The toxicogenomic multiverse: convergent recruitment of proteins into animal venoms.

Science.gov (United States)

Fry, Bryan G; Roelants, Kim; Champagne, Donald E; Scheib, Holger; Tyndall, Joel D A; King, Glenn F; Nevalainen, Timo J; Norman, Janette A; Lewis, Richard J; Norton, Raymond S; Renjifo, Camila; de la Vega, Ricardo C Rodríguez

2009-01-01

Throughout evolution, numerous proteins have been convergently recruited into the venoms of various animals, including centipedes, cephalopods, cone snails, fish, insects (several independent venom systems), platypus, scorpions, shrews, spiders, toxicoferan reptiles (lizards and snakes), and sea anemones. The protein scaffolds utilized convergently have included AVIT/colipase/prokineticin, CAP, chitinase, cystatin, defensins, hyaluronidase, Kunitz, lectin, lipocalin, natriuretic peptide, peptidase S1, phospholipase A(2), sphingomyelinase D, and SPRY. Many of these same venom protein types have also been convergently recruited for use in the hematophagous gland secretions of invertebrates (e.g., fleas, leeches, kissing bugs, mosquitoes, and ticks) and vertebrates (e.g., vampire bats). Here, we discuss a number of overarching structural, functional, and evolutionary generalities of the protein families from which these toxins have been frequently recruited and propose a revised and expanded working definition for venom. Given the large number of striking similarities between the protein compositions of conventional venoms and hematophagous secretions, we argue that the latter should also fall under the same definition.

Recruitment of phosphorylated small heat shock protein Hsp27 to nuclear speckles without stress

International Nuclear Information System (INIS)

Bryantsev, A.L.; Chechenova, M.B.; Shelden, E.A.

2007-01-01

During stress, the mammalian small heat shock protein Hsp27 enters cell nuclei. The present study examines the requirements for entry of Hsp27 into nuclei of normal rat kidney (NRK) renal epithelial cells, and for its interactions with specific nuclear structures. We find that phosphorylation of Hsp27 is necessary for the efficient entry into nuclei during heat shock but not sufficient for efficient nuclear entry under control conditions. We further report that Hsp27 is recruited to an RNAse sensitive fraction of SC35 positive nuclear speckles, but not other intranuclear structures, in response to heat shock. Intriguingly, Hsp27 phosphorylation, in the absence of stress, is sufficient for recruitment to speckles found in post-anaphase stage mitotic cells. Additionally, pseudophosphorylated Hsp27 fused to a nuclear localization peptide (NLS) is recruited to nuclear speckles in unstressed interphase cells, but wildtype and nonphosphorylatable Hsp27 NLS fusion proteins are not. The expression of NLS-Hsp27 mutants does not enhance colony forming abilities of cells subjected to severe heat shock, but does regulate nuclear speckle morphology. These data demonstrate that phosphorylation, but not stress, mediates Hsp27 recruitment to an RNAse soluble fraction of nuclear speckles and support a site-specific role for Hsp27 within the nucleus

Comparative proteomics reveals key proteins recruited at the nucleoid of Deinococcus after irradiation-induced DNA damage

International Nuclear Information System (INIS)

Bouthier de la Tour, Claire; Passot, Fanny Marie; Toueille, Magali; Servant, Pascale; Sommer, Suzanne; Mirabella, Boris; Blanchard, Laurence; Groot, Arjan de; Guerin, Philippe; Armengaud, Jean

2013-01-01

The nucleoids of radiation-resistant Deinococcus species show a high degree of compaction maintained after ionizing irradiation. We identified proteins recruited after irradiation in nucleoids of Deinococcus radiodurans and Deinococcus deserti by means of comparative proteomics. Proteins in nucleoid-enriched fractions from unirradiated and irradiated Deinococcus were identified and semi quantified by shotgun proteomics. The ssDNA-binding protein SSB, DNA gyrase subunits GyrA and GyrB, DNA topoisomerase I, RecA recombinase, UvrA excinuclease, RecQ helicase, DdrA, DdrB, and DdrD proteins were found in significantly higher amounts in irradiated nucleoids of both Deinococcus species. We observed, by immunofluorescence microscopy, the subcellular localization of these proteins in D. radiodurans, showing for the first time the recruitment of the DdrD protein into the D. radiodurans nucleoid. We specifically followed the kinetics of recruitment of RecA, DdrA, and DdrD to the nucleoid after irradiation. Remarkably, RecA proteins formed irregular filament-like structures 1 h after irradiation, before being redistributed throughout the cells by 3 h post-irradiation. Comparable dynamics of DdrD localization were observed, suggesting a possible functional interaction between RecA and DdrD. Several proteins involved in nucleotide synthesis were also seen in higher quantities in the nucleoids of irradiated cells, indicative of the existence of a mechanism for orchestrating the presence of proteins involved in DNA metabolism in nucleoids in response to massive DNA damage. All MS data have been deposited in the ProteomeXchange with identifier PXD00196. (authors)

Proteins with Intrinsically Disordered Domains Are Preferentially Recruited to Polyglutamine Aggregates.

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Maggie P Wear

Full Text Available Intracellular protein aggregation is the hallmark of several neurodegenerative diseases. Aggregates formed by polyglutamine (polyQ-expanded proteins, such as Huntingtin, adopt amyloid-like structures that are resistant to denaturation. We used a novel purification strategy to isolate aggregates formed by human Huntingtin N-terminal fragments with expanded polyQ tracts from both yeast and mammalian (PC-12 cells. Using mass spectrometry we identified the protein species that are trapped within these polyQ aggregates. We found that proteins with very long intrinsically-disordered (ID domains (≥ 100 amino acids and RNA-binding proteins were disproportionately recruited into aggregates. The removal of the ID domains from selected proteins was sufficient to eliminate their recruitment into polyQ aggregates. We also observed that several neurodegenerative disease-linked proteins were reproducibly trapped within the polyQ aggregates purified from mammalian cells. Many of these proteins have large ID domains and are found in neuronal inclusions in their respective diseases. Our study indicates that neurodegenerative disease-associated proteins are particularly vulnerable to recruitment into polyQ aggregates via their ID domains. Also, the high frequency of ID domains in RNA-binding proteins may explain why RNA-binding proteins are frequently found in pathological inclusions in various neurodegenerative diseases.

Specificity of molecular interactions in transient protein-protein interaction interfaces.

Science.gov (United States)

Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

Receptor-interacting protein (RIP) kinase family

Science.gov (United States)

Zhang, Duanwu; Lin, Juan; Han, Jiahuai

2010-01-01

Receptor-interacting protein (RIP) kinases are a group of threonine/serine protein kinases with a relatively conserved kinase domain but distinct non-kinase regions. A number of different domain structures, such as death and caspase activation and recruitment domain (CARD) domains, were found in different RIP family members, and these domains should be keys in determining the specific function of each RIP kinase. It is known that RIP kinases participate in different biological processes, including those in innate immunity, but their downstream substrates are largely unknown. This review will give an overview of the structures and functions of RIP family members, and an update of recent progress in RIP kinase research. PMID:20383176

Coordination of the recruitment of the FANCD2 and PALB2 Fanconi anemia proteins by an ubiquitin signaling network.

Science.gov (United States)

Bick, Gregory; Zhang, Fan; Meetei, A Ruhikanta; Andreassen, Paul R

2017-06-01

Fanconi anemia (FA) is a chromosome instability syndrome and the 20 identified FA proteins are organized into two main arms which are thought to function at distinct steps in the repair of DNA interstrand crosslinks (ICLs). These two arms include the upstream FA pathway, which culminates in the monoubiquitination of FANCD2 and FANCI, and downstream breast cancer (BRCA)-associated proteins that interact in protein complexes. How, and whether, these two groups of FA proteins are integrated is unclear. Here, we show that FANCD2 and PALB2, as indicators of the upstream and downstream arms, respectively, colocalize independently of each other in response to DNA damage induced by mitomycin C (MMC). We also show that ubiquitin chains are induced by MMC and colocalize with both FANCD2 and PALB2. Our finding that the RNF8 E3 ligase has a role in recruiting FANCD2 and PALB2 also provides support for the hypothesis that the two branches of the FA-BRCA pathway are coordinated by ubiquitin signaling. Interestingly, we find that the RNF8 partner, MDC1, as well as the ubiquitin-binding protein, RAP80, specifically recruit PALB2, while a different ubiquitin-binding protein, FAAP20, functions only in the recruitment of FANCD2. Thus, FANCD2 and PALB2 are not recruited in a single linear pathway, rather we define how their localization is coordinated and integrated by a network of ubiquitin-related proteins. We propose that such regulation may enable upstream and downstream FA proteins to act at distinct steps in the repair of ICLs.

Single-strand DNA binding protein SSB1 facilitates TERT recruitment to telomeres and maintains telomere G-overhangs

Science.gov (United States)

Pandita, Raj K.; Chow, Tracy T.; Udayakumar, Durga; Bain, Amanda L.; Cubeddu, Liza; Hunt, Clayton R.; Shi, Wei; Horikoshi, Nobuo; Zhao, Yong; Wright, Woodring E.; Khanna, Kum Kum; Shay, Jerry W.; Pandita, Tej K.

2015-01-01

Proliferating mammalian stem and cancer cells express telomerase (TERT) in an effort to extend chromosomal G-overhangs and maintain telomere ends. Telomerase-expressing cells also have higher levels of the single-stranded DNA binding protein SSB1, which has a critical role in DNA double-strand break repair. Here we report that SSB1 binds specifically to G-strand telomeric DNA in vitro and associates with telomeres in vivo. SSB1 interacted with the TERT catalytic subunit and regulates its interaction with telomeres. Deletion of SSB1 reduced TERT interaction with telomeres and lead to G-overhang loss. While SSB1 was recruited to DSB sites, we found no corresponding change in TERT levels at these sites, implying that SSB1-TERT interaction relied upon a specific chromatin structure or context. Our findings offer an explanation for how telomerase is recruited to telomeres to facilitate G-strand DNA extension, a critical step in maintaining telomere ends and cell viability in all cancer cells. PMID:25589350

A recruiting protein of geranylgeranyl diphosphate synthase controls metabolic flux toward chlorophyll biosynthesis in rice.

Science.gov (United States)

Zhou, Fei; Wang, Cheng-Yuan; Gutensohn, Michael; Jiang, Ling; Zhang, Peng; Zhang, Dabing; Dudareva, Natalia; Lu, Shan

2017-06-27

In plants, geranylgeranyl diphosphate (GGPP) is produced by plastidic GGPP synthase (GGPPS) and serves as a precursor for vital metabolic branches, including chlorophyll, carotenoid, and gibberellin biosynthesis. However, molecular mechanisms regulating GGPP allocation among these biosynthetic pathways localized in the same subcellular compartment are largely unknown. We found that rice contains only one functionally active GGPPS, OsGGPPS1, in chloroplasts. A functionally active homodimeric enzyme composed of two OsGGPPS1 subunits is located in the stroma. In thylakoid membranes, however, the GGPPS activity resides in a heterodimeric enzyme composed of one OsGGPPS1 subunit and GGPPS recruiting protein (OsGRP). OsGRP is structurally most similar to members of the geranyl diphosphate synthase small subunit type II subfamily. In contrast to members of this subfamily, OsGRP enhances OsGGPPS1 catalytic efficiency and specificity of GGPP production on interaction with OsGGPPS1. Structural biology and protein interaction analyses demonstrate that affinity between OsGRP and OsGGPPS1 is stronger than between two OsGGPPS1 molecules in homodimers. OsGRP determines OsGGPPS1 suborganellar localization and directs it to a large protein complex in thylakoid membranes, consisting of geranylgeranyl reductase (OsGGR), light-harvesting-like protein 3 (OsLIL3), protochlorophyllide oxidoreductase (OsPORB), and chlorophyll synthase (OsCHLG). Taken together, genetic and biochemical analyses suggest OsGRP functions in recruiting OsGGPPS1 from the stroma toward thylakoid membranes, thus providing a mechanism to control GGPP flux toward chlorophyll biosynthesis.

Shwachman-Diamond Syndrome Protein SBDS Maintains Human Telomeres by Regulating Telomerase Recruitment

Directory of Open Access Journals (Sweden)

Yi Liu

2018-02-01

Full Text Available Shwachman-Diamond syndrome (SDS is a rare pediatric disease characterized by various systemic disorders, including hematopoietic dysfunction. The mutation of Shwachman-Bodian-Diamond syndrome (SBDS gene has been proposed to be a major causative reason for SDS. Although SBDS patients were reported to have shorter telomere length in granulocytes, the underlying mechanism is still unclear. Here we provide data to elucidate the role of SBDS in telomere protection. We demonstrate that SBDS deficiency leads to telomere shortening. We found that overexpression of disease-associated SBDS mutants or knockdown of SBDS hampered the recruitment of telomerase onto telomeres, while the overall reverse transcriptase activity of telomerase remained unaffected. Moreover, we show that SBDS could specifically bind to TPP1 during the S phase of cell cycle, likely functioning as a stabilizer for TPP1-telomerase interaction. Our findings suggest that SBDS is a telomere-protecting protein that participates in regulating telomerase recruitment.

Single-strand DNA-binding protein SSB1 facilitates TERT recruitment to telomeres and maintains telomere G-overhangs.

Science.gov (United States)

Pandita, Raj K; Chow, Tracy T; Udayakumar, Durga; Bain, Amanda L; Cubeddu, Liza; Hunt, Clayton R; Shi, Wei; Horikoshi, Nobuo; Zhao, Yong; Wright, Woodring E; Khanna, Kum Kum; Shay, Jerry W; Pandita, Tej K

2015-03-01

Proliferating mammalian stem and cancer cells express telomerase [telomerase reverse transcriptase (TERT)] in an effort to extend chromosomal G-overhangs and maintain telomere ends. Telomerase-expressing cells also have higher levels of the single-stranded DNA-binding protein SSB1, which has a critical role in DNA double-strand break (DSB) repair. Here, we report that SSB1 binds specifically to G-strand telomeric DNA in vitro and associates with telomeres in vivo. SSB1 interacts with the TERT catalytic subunit and regulates its interaction with telomeres. Deletion of SSB1 reduces TERT interaction with telomeres and leads to G-overhang loss. Although SSB1 is recruited to DSB sites, we found no corresponding change in TERT levels at these sites, implying that SSB1-TERT interaction relies upon a specific chromatin structure or context. Our findings offer an explanation for how telomerase is recruited to telomeres to facilitate G-strand DNA extension, a critical step in maintaining telomere ends and cell viability in all cancer cells. Cancer Res; 75(5); 858-69. ©2015 AACR. ©2015 American Association for Cancer Research.

The RSF1 histone-remodelling factor facilitates DNA double-strand break repair by recruiting centromeric and Fanconi Anaemia proteins.

Directory of Open Access Journals (Sweden)

Fabio Pessina

2014-05-01

Full Text Available ATM is a central regulator of the cellular responses to DNA double-strand breaks (DSBs. Here we identify a biochemical interaction between ATM and RSF1 and we characterise the role of RSF1 in this response. The ATM-RSF1 interaction is dependent upon both DSBs and ATM kinase activity. Together with SNF2H/SMARCA5, RSF1 forms the RSF chromatin-remodelling complex. Although RSF1 is specific to the RSF complex, SNF2H/SMARCA5 is a catalytic subunit of several other chromatin-remodelling complexes. Although not required for checkpoint signalling, RSF1 is required for efficient repair of DSBs via both end-joining and homology-directed repair. Specifically, the ATM-dependent recruitment to sites of DSBs of the histone fold proteins CENPS/MHF1 and CENPX/MHF2, previously identified at centromeres, is RSF1-dependent. In turn these proteins recruit and regulate the mono-ubiquitination of the Fanconi Anaemia proteins FANCD2 and FANCI. We propose that by depositing CENPS/MHF1 and CENPX/MHF2, the RSF complex either directly or indirectly contributes to the reorganisation of chromatin around DSBs that is required for efficient DNA repair.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Characterization of MRP RNA-protein interactions within the perinucleolar compartment.

Science.gov (United States)

Pollock, Callie; Daily, Kelly; Nguyen, Van Trung; Wang, Chen; Lewandowska, Marzena Anna; Bensaude, Olivier; Huang, Sui

2011-03-15

The perinucleolar compartment (PNC) forms in cancer cells and is highly enriched with a subset of polymerase III RNAs and RNA-binding proteins. Here we report that PNC components mitochondrial RNA-processing (MRP) RNA, pyrimidine tract-binding protein (PTB), and CUG-binding protein (CUGBP) interact in vivo, as demonstrated by coimmunoprecipitation and RNA pull-down experiments. Glycerol gradient analyses show that this complex is large and sediments at a different fraction from known MRP RNA-containing complexes, the MRP ribonucleoprotein ribozyme and human telomerase reverse transcriptase. Tethering PNC components to a LacO locus recruits other PNC components, further confirming the in vivo interactions. These interactions are present both in PNC-containing and -lacking cells. High-resolution localization analyses demonstrate that MRP RNA, CUGBP, and PTB colocalize at the PNC as a reticulated network, intertwining with newly synthesized RNA. Furthermore, green fluorescent protein (GFP)-PTB and GFP-CUGBP show a slower rate of fluorescence recovery after photobleaching at the PNC than in the nucleoplasm, illustrating the different molecular interaction of the complexes associated with the PNC. These findings support a working model in which the MRP RNA-protein complex becomes nucleated at the PNC in cancer cells and may play a role in gene expression regulation at the DNA locus that associates with the PNC.

Aquaporin Protein-Protein Interactions

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Jennifer Virginia Roche

2017-10-01

Full Text Available Aquaporins are tetrameric membrane-bound channels that facilitate transport of water and other small solutes across cell membranes. In eukaryotes, they are frequently regulated by gating or trafficking, allowing for the cell to control membrane permeability in a specific manner. Protein–protein interactions play crucial roles in both regulatory processes and also mediate alternative functions such as cell adhesion. In this review, we summarize recent knowledge about aquaporin protein–protein interactions; dividing the interactions into three types: (1 interactions between aquaporin tetramers; (2 interactions between aquaporin monomers within a tetramer (hetero-tetramerization; and (3 transient interactions with regulatory proteins. We particularly focus on the structural aspects of the interactions, discussing the small differences within a conserved overall fold that allow for aquaporins to be differentially regulated in an organism-, tissue- and trigger-specific manner. A deep knowledge about these differences is needed to fully understand aquaporin function and regulation in many physiological processes, and may enable design of compounds targeting specific aquaporins for treatment of human disease.

Cyclic adenosine 3',5'-monophosphate (cAMP) enhances cAMP-responsive element binding (CREB) protein phosphorylation and phospho-CREB interaction with the mouse steroidogenic acute regulatory protein gene promoter.

Science.gov (United States)

Clem, Brian F; Hudson, Elizabeth A; Clark, Barbara J

2005-03-01

Steroidogenic acute regulatory protein (StAR) transcription is regulated through cAMP-protein kinase A-dependent mechanisms that involve multiple transcription factors including the cAMP-responsive element binding protein (CREB) family members. Classically, binding of phosphorylated CREB to cis-acting cAMP-responsive elements (5'-TGACGTCA-3') within target gene promoters leads to recruitment of the coactivator CREB binding protein (CBP). Herein we examined the extent of CREB family member phosphorylation on protein-DNA interactions and CBP recruitment with the StAR promoter. Immunoblot analysis revealed that CREB, cAMP-responsive element modulator (CREM), and activating transcription factor (ATF)-1 are expressed in MA-10 mouse Leydig tumor cells, yet only CREB and ATF-1 are phosphorylated. (Bu)2cAMP treatment of MA-10 cells increased CREB phosphorylation approximately 2.3-fold within 30 min but did not change total nuclear CREB expression levels. Using DNA-affinity chromatography, we now show that CREB and ATF-1, but not CREM, interact with the StAR promoter, and this interaction is dependent on the activator protein-1 (AP-1) cis-acting element within the cAMP-responsive region. In addition, (Bu)2cAMP-treatment increased phosphorylated CREB (P-CREB) association with the StAR promoter but did not influence total CREB interaction. In vivo chromatin immunoprecipitation assays demonstrated CREB binding to the StAR proximal promoter is independent of (Bu)2cAMP-treatment, confirming our in vitro analysis. However, (Bu)2cAMP-treatment increased P-CREB and CBP interaction with the StAR promoter, demonstrating for the first time the physical role of P-CREB:DNA interactions in CBP recruitment to the StAR proximal promoter.

Our interests in protein-protein interactions

Indian Academy of Sciences (India)

protein interactions. Evolution of P-P partnerships. Evolution of P-P structures. Evolutionary dynamics of P-P interactions. Dynamics of P-P interaction network. Host-pathogen interactions. CryoEM mapping of gigantic protein assemblies.

Evolution of protein-protein interactions

Indian Academy of Sciences (India)

Evolution of protein-protein interactions · Our interests in protein-protein interactions · Slide 3 · Slide 4 · Slide 5 · Slide 6 · Slide 7 · Slide 8 · Slide 9 · Slide 10 · Slide 11 · Slide 12 · Slide 13 · Slide 14 · Slide 15 · Slide 16 · Slide 17 · Slide 18 · Slide 19 · Slide 20.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

Science.gov (United States)

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Non-interacting surface solvation and dynamics in protein-protein interactions

NARCIS (Netherlands)

Visscher, Koen M.; Kastritis, Panagiotis L.|info:eu-repo/dai/nl/315886668; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238

2015-01-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo

Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

Directory of Open Access Journals (Sweden)

Susan Khor

Full Text Available Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

Science.gov (United States)

Khor, Susan

2014-01-01

Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

Kinase Substrate Sensor (KISS), a mammalian in situ protein interaction sensor.

Science.gov (United States)

Lievens, Sam; Gerlo, Sarah; Lemmens, Irma; De Clercq, Dries J H; Risseeuw, Martijn D P; Vanderroost, Nele; De Smet, Anne-Sophie; Ruyssinck, Elien; Chevet, Eric; Van Calenbergh, Serge; Tavernier, Jan

2014-12-01

Probably every cellular process is governed by protein-protein interaction (PPIs), which are often highly dynamic in nature being modulated by in- or external stimuli. Here we present KISS, for KInase Substrate Sensor, a mammalian two-hybrid approach designed to map intracellular PPIs and some of the dynamic features they exhibit. Benchmarking experiments indicate that in terms of sensitivity and specificity KISS is on par with other binary protein interaction technologies while being complementary with regard to the subset of PPIs it is able to detect. We used KISS to evaluate interactions between different types of proteins, including transmembrane proteins, expressed at their native subcellular location. In situ analysis of endoplasmic reticulum stress-induced clustering of the endoplasmic reticulum stress sensor ERN1 and ligand-dependent β-arrestin recruitment to GPCRs illustrated the method's potential to study functional PPI modulation in complex cellular processes. Exploring its use as a tool for in cell evaluation of pharmacological interference with PPIs, we showed that reported effects of known GPCR antagonists and PPI inhibitors are properly recapitulated. In a three-hybrid setup, KISS was able to map interactions between small molecules and proteins. Taken together, we established KISS as a sensitive approach for in situ analysis of protein interactions and their modulation in a changing cellular context or in response to pharmacological challenges. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Characterization of MRP RNA–protein interactions within the perinucleolar compartment

Science.gov (United States)

Pollock, Callie; Daily, Kelly; Nguyen, Van Trung; Wang, Chen; Lewandowska, Marzena Anna; Bensaude, Olivier; Huang, Sui

2011-01-01

The perinucleolar compartment (PNC) forms in cancer cells and is highly enriched with a subset of polymerase III RNAs and RNA-binding proteins. Here we report that PNC components mitochondrial RNA–processing (MRP) RNA, pyrimidine tract–binding protein (PTB), and CUG-binding protein (CUGBP) interact in vivo, as demonstrated by coimmunoprecipitation and RNA pull-down experiments. Glycerol gradient analyses show that this complex is large and sediments at a different fraction from known MRP RNA–containing complexes, the MRP ribonucleoprotein ribozyme and human telomerase reverse transcriptase. Tethering PNC components to a LacO locus recruits other PNC components, further confirming the in vivo interactions. These interactions are present both in PNC-containing and -lacking cells. High-resolution localization analyses demonstrate that MRP RNA, CUGBP, and PTB colocalize at the PNC as a reticulated network, intertwining with newly synthesized RNA. Furthermore, green fluorescent protein (GFP)–PTB and GFP-CUGBP show a slower rate of fluorescence recovery after photobleaching at the PNC than in the nucleoplasm, illustrating the different molecular interaction of the complexes associated with the PNC. These findings support a working model in which the MRP RNA–protein complex becomes nucleated at the PNC in cancer cells and may play a role in gene expression regulation at the DNA locus that associates with the PNC. PMID:21233287

HTLV-1 Tax protein recruitment into IKKε and TBK1 kinase complexes enhances IFN-I expression.

Science.gov (United States)

Diani, Erica; Avesani, Francesca; Bergamo, Elisa; Cremonese, Giorgia; Bertazzoni, Umberto; Romanelli, Maria Grazia

2015-02-01

The Tax protein expressed by human T-cell leukemia virus type 1 (HTLV-1) plays a pivotal role in the deregulation of cellular pathways involved in the immune response, inflammation, cell survival, and cancer. Many of these effects derive from Tax multiple interactions with host factors, including the subunits of the IKK-complex that are required for NF-κB activation. IKKɛ and TBK1 are two IKK-related kinases that allow the phosphorylation of interferon regulatory factors that trigger IFN type I gene expression. We observed that IKKɛ and TBK1 recruit Tax into cellular immunocomplexes. We also found that TRAF3, which regulates cell receptor signaling effectors, forms complexes with Tax. Transactivation analyses revealed that expression of Tax, in presence of IKKɛ and TBK1, enhances IFN-β promoter activity, whereas the activation of NF-κB promoter is not modified. We propose that Tax may be recruited into the TBK1/IKKɛ complexes as a scaffolding-adaptor protein that enhances IFN-I gene expression. Copyright © 2014 Elsevier Inc. All rights reserved.

Mechanism of Archaeal MCM Helicase Recruitment to DNA Replication Origins

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Samson, Rachel Y.; Abeyrathne, Priyanka D.; Bell, Stephen D.

2015-01-01

Summary Cellular DNA replication origins direct the recruitment of replicative helicases via the action of initiator proteins belonging to the AAA+ superfamily of ATPases. Archaea have a simplified subset of the eukaryotic DNA replication machinery proteins and possess initiators that appear ancestral to both eukaryotic Orc1 and Cdc6. We have reconstituted origin-dependent recruitment of the homohexameric archaeal MCM in vitro with purified recombinant proteins. Using this system, we reveal that archaeal Orc1-1 fulfills both Orc1 and Cdc6 functions by binding to a replication origin and directly recruiting MCM helicase. We identify the interaction interface between these proteins and reveal how ATP binding by Orc1-1 modulates recruitment of MCM. Additionally, we provide evidence that an open-ring form of the archaeal MCM homohexamer is loaded at origins. PMID:26725007

Bioinformatic Prediction of WSSV-Host Protein-Protein Interaction

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Zheng Sun

2014-01-01

Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.

The antituberculosis antibiotic capreomycin inhibits protein synthesis by disrupting interaction between ribosomal proteins L12 and L10.

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Lin, Yuan; Li, Yan; Zhu, Ningyu; Han, Yanxing; Jiang, Wei; Wang, Yanchang; Si, Shuyi; Jiang, Jiandong

2014-01-01

Capreomycin is a second-line drug for multiple-drug-resistant tuberculosis (TB). However, with increased use in clinics, the therapeutic efficiency of capreomycin is decreasing. To better understand TB resistance to capreomycin, we have done research to identify the molecular target of capreomycin. Mycobacterium tuberculosis ribosomal proteins L12 and L10 interact with each other and constitute the stalk of the 50S ribosomal subunit, which recruits initiation and elongation factors during translation. Hence, the L12-L10 interaction is considered to be essential for ribosomal function and protein synthesis. Here we provide evidence showing that capreomycin inhibits the L12-L10 interaction by using an established L12-L10 interaction assay. Overexpression of L12 and/or L10 in M. smegmatis, a species close to M. tuberculosis, increases the MIC of capreomycin. Moreover, both elongation factor G-dependent GTPase activity and ribosome-mediated protein synthesis are inhibited by capreomycin. When protein synthesis was blocked with thiostrepton, however, the bactericidal activity of capreomycin was restrained. All of these results suggest that capreomycin seems to inhibit TB by interrupting the L12-L10 interaction. This finding might provide novel clues for anti-TB drug discovery.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

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Ching-Tai Chen

Full Text Available Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins and were tested on an independent dataset (consisting of 142 proteins. The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

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Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

Argonaute Utilization for miRNA Silencing Is Determined by Phosphorylation-Dependent Recruitment of LIM-Domain-Containing Proteins

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Katherine S. Bridge

2017-07-01

Full Text Available As core components of the microRNA-induced silencing complex (miRISC, Argonaute (AGO proteins interact with TNRC6 proteins, recruiting other effectors of translational repression/mRNA destabilization. Here, we show that LIMD1 coordinates the assembly of an AGO-TNRC6 containing miRISC complex by binding both proteins simultaneously at distinct interfaces. Phosphorylation of AGO2 at Ser 387 by Akt3 induces LIMD1 binding, which in turn enables AGO2 to interact with TNRC6A and downstream effector DDX6. Conservation of this serine in AGO1 and 4 indicates this mechanism may be a fundamental requirement for AGO function and miRISC assembly. Upon CRISPR-Cas9-mediated knockout of LIMD1, AGO2 miRNA-silencing function is lost and miRNA silencing becomes dependent on a complex formed by AGO3 and the LIMD1 family member WTIP. The switch to AGO3 utilization occurs due to the presence of a glutamic acid residue (E390 on the interaction interface, which allows AGO3 to bind to LIMD1, AJUBA, and WTIP irrespective of Akt signaling.

Recruitment of focal adhesion kinase and paxillin to β1 integrin promotes cancer cell migration via mitogen activated protein kinase activation

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Crowe, David L; Ohannessian, Arthur

2004-01-01

Integrin-extracellular matrix interactions activate signaling cascades such as mitogen activated protein kinases (MAPK). Integrin binding to extracellular matrix increases tyrosine phosphorylation of focal adhesion kinase (FAK). Inhibition of FAK activity by expression of its carboxyl terminus decreases cell motility, and cells from FAK deficient mice also show reduced migration. Paxillin is a focal adhesion protein which is also phosphorylated on tyrosine. FAK recruitment of paxillin to the cell membrane correlates with Shc phosphorylation and activation of MAPK. Decreased FAK expression inhibits papilloma formation in a mouse skin carcinogenesis model. We previously demonstrated that MAPK activation was required for growth factor induced in vitro migration and invasion by human squamous cell carcinoma (SCC) lines. Adapter protein recruitment to integrin subunits was examined by co-immunoprecipitation in SCC cells attached to type IV collagen or plastic. Stable clones overexpressing FAK or paxillin were created using the lipofection technique. Modified Boyden chambers were used for invasion assays. In the present study, we showed that FAK and paxillin but not Shc are recruited to the β1 integrin cytoplasmic domain following attachment of SCC cells to type IV collagen. Overexpression of either FAK or paxillin stimulated cancer cell migration on type IV collagen and invasion through reconstituted basement membrane which was dependent on MAPK activity. We concluded that recruitment of focal adhesion kinase and paxillin to β1 integrin promoted cancer cell migration via the mitogen activated protein kinase pathway

Recruitment of focal adhesion kinase and paxillin to β1 integrin promotes cancer cell migration via mitogen activated protein kinase activation

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Ohannessian Arthur

2004-05-01

Full Text Available Abstract Background Integrin-extracellular matrix interactions activate signaling cascades such as mitogen activated protein kinases (MAPK. Integrin binding to extracellular matrix increases tyrosine phosphorylation of focal adhesion kinase (FAK. Inhibition of FAK activity by expression of its carboxyl terminus decreases cell motility, and cells from FAK deficient mice also show reduced migration. Paxillin is a focal adhesion protein which is also phosphorylated on tyrosine. FAK recruitment of paxillin to the cell membrane correlates with Shc phosphorylation and activation of MAPK. Decreased FAK expression inhibits papilloma formation in a mouse skin carcinogenesis model. We previously demonstrated that MAPK activation was required for growth factor induced in vitro migration and invasion by human squamous cell carcinoma (SCC lines. Methods Adapter protein recruitment to integrin subunits was examined by co-immunoprecipitation in SCC cells attached to type IV collagen or plastic. Stable clones overexpressing FAK or paxillin were created using the lipofection technique. Modified Boyden chambers were used for invasion assays. Results In the present study, we showed that FAK and paxillin but not Shc are recruited to the β1 integrin cytoplasmic domain following attachment of SCC cells to type IV collagen. Overexpression of either FAK or paxillin stimulated cancer cell migration on type IV collagen and invasion through reconstituted basement membrane which was dependent on MAPK activity. Conclusions We concluded that recruitment of focal adhesion kinase and paxillin to β1 integrin promoted cancer cell migration via the mitogen activated protein kinase pathway.

Specificity and affinity quantification of protein-protein interactions.

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Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

2013-05-01

Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

Information assessment on predicting protein-protein interactions

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Gerstein Mark

2004-10-01

Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

Host and bacterial proteins that repress recruitment of LC3 to Shigella early during infection.

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Leigh A Baxt

Full Text Available Shigella spp. are intracytosolic gram-negative pathogens that cause disease by invasion and spread through the colonic mucosa, utilizing host cytoskeletal components to form propulsive actin tails. We have previously identified the host factor Toca-1 as being recruited to intracellular S. flexneri and being required for efficient bacterial actin tail formation. We show that at early times during infection (40 min., the type three-secreted effector protein IcsB recruits Toca-1 to intracellular bacteria and that recruitment of Toca-1 is associated with repression of recruitment of LC3, as well as with repression of recruitment of the autophagy marker NDP52, around these intracellular bacteria. LC3 is best characterized as a marker of autophagosomes, but also marks phagosomal membranes in the process LC3-associated phagocytosis. IcsB has previously been demonstrated to be required for S. flexneri evasion of autophagy at late times during infection (4-6 hr by inhibiting binding of the autophagy protein Atg5 to the Shigella surface protein IcsA (VirG. Our results suggest that IcsB and Toca-1 modulation of LC3 recruitment restricts LC3-associated phagocytosis and/or LC3 recruitment to vacuolar membrane remnants. Together with published results, our findings suggest that IcsB inhibits innate immune responses in two distinct ways, first, by inhibiting LC3-associated phagocytosis and/or LC3 recruitment to vacuolar membrane remnants early during infection, and second, by inhibiting autophagy late during infection.

Understanding Protein-Protein Interactions Using Local Structural Features

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Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

Evolutionary reprograming of protein-protein interaction specificity.

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Akiva, Eyal; Babbitt, Patricia C

2015-10-22

Using mutation libraries and deep sequencing, Aakre et al. study the evolution of protein-protein interactions using a toxin-antitoxin model. The results indicate probable trajectories via "intermediate" proteins that are promiscuous, thus avoiding transitions via non-interactions. These results extend observations about other biological interactions and enzyme evolution, suggesting broadly general principles. Copyright © 2015 Elsevier Inc. All rights reserved.

Rab11-family of interacting protein 2 associates with chlamydial inclusions through its Rab-binding domain and promotes bacterial multiplication.

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Leiva, Natalia; Capmany, Anahí; Damiani, María Teresa

2013-01-01

Chlamydia trachomatis, an obligate intracellular pathogen, survives within host cells in a special compartment named 'inclusion' and takes advantage of host vesicular transport pathways for its growth and replication. Rab GTPases are key regulatory proteins of intracellular trafficking. Several Rabs, among them Rab11 and Rab14, are implicated in chlamydial development. FIP2, a member of the Rab11-Family of Interacting Proteins, presents at the C-terminus a Rab-binding domain that interacts with both Rab11 and Rab14. In this study, we determined and characterized the recruitment of endogenous and GFP-tagged FIP2 to the chlamydial inclusions. The recruitment of FIP2 is specific since other members of the Rab11-Family of Interacting Proteins do not associate with the chlamydial inclusions. The Rab-binding domain of FIP2 is essential for its association. Our results indicate that FIP2 binds to Rab11 at the chlamydial inclusion membrane through its Rab-binding domain. The presence of FIP2 at the chlamydial inclusion favours the recruitment of Rab14. Furthermore, our results show that FIP2 promotes inclusion development and bacterial replication. In agreement, the silencing of FIP2 decreases the bacterial progeny. C. trachomatis likely recruits FIP2 to hijack host intracellular trafficking to redirect vesicles full of nutrients towards the inclusion. © 2012 Blackwell Publishing Ltd.

Mapping Protein-Protein Interactions by Quantitative Proteomics

DEFF Research Database (Denmark)

Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

2010-01-01

spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...... to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions.......Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...

Protein- protein interaction detection system using fluorescent protein microdomains

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Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

Plasma membrane lipid–protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana

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Zauber, Henrik; Burgos, Asdrubal; Garapati, Prashanth; Schulze, Waltraud X.

2014-01-01

The plasma membrane is an important organelle providing structure, signaling and transport as major biological functions. Being composed of lipids and proteins with different physicochemical properties, the biological functions of membranes depend on specific protein–protein and protein–lipid interactions. Interactions of proteins with their specific sterol and lipid environment were shown to be important factors for protein recruitment into sub-compartmental structures of the plasma membrane. System-wide implications of altered endogenous sterol levels for membrane functions in living cells were not studied in higher plant cells. In particular, little is known how alterations in membrane sterol composition affect protein and lipid organization and interaction within membranes. Here, we conducted a comparative analysis of the plasma membrane protein and lipid composition in Arabidopsis sterol-biosynthesis mutants smt1 and ugt80A2;B1. smt1 shows general alterations in sterol composition while ugt80A2;B1 is significantly impaired in sterol glycosylation. By systematically analyzing different cellular fractions and combining proteomic with lipidomic data we were able to reveal contrasting alterations in lipid–protein interactions in both mutants, with resulting differential changes in plasma membrane signaling status. PMID:24672530

Oligomeric protein structure networks: insights into protein-protein interactions

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Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Human cancer protein-protein interaction network: a structural perspective.

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Gozde Kar

2009-12-01

Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

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Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

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Greenblatt Jack

2006-07-01

Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

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Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

An ontology-based search engine for protein-protein interactions.

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Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

Alba-domain proteins of Trypanosoma brucei are cytoplasmic RNA-binding proteins that interact with the translation machinery.

Directory of Open Access Journals (Sweden)

Jan Mani

Full Text Available Trypanosoma brucei and related pathogens transcribe most genes as polycistronic arrays that are subsequently processed into monocistronic mRNAs. Expression is frequently regulated post-transcriptionally by cis-acting elements in the untranslated regions (UTRs. GPEET and EP procyclins are the major surface proteins of procyclic (insect midgut forms of T. brucei. Three regulatory elements common to the 3' UTRs of both mRNAs regulate mRNA turnover and translation. The glycerol-responsive element (GRE is unique to the GPEET 3' UTR and regulates its expression independently from EP. A synthetic RNA encompassing the GRE showed robust sequence-specific interactions with cytoplasmic proteins in electromobility shift assays. This, combined with column chromatography, led to the identification of 3 Alba-domain proteins. RNAi against Alba3 caused a growth phenotype and reduced the levels of Alba1 and Alba2 proteins, indicative of interactions between family members. Tandem-affinity purification and co-immunoprecipitation verified these interactions and also identified Alba4 in sub-stoichiometric amounts. Alba proteins are cytoplasmic and are recruited to starvation granules together with poly(A RNA. Concomitant depletion of all four Alba proteins by RNAi specifically reduced translation of a reporter transcript flanked by the GPEET 3' UTR. Pulldown of tagged Alba proteins confirmed interactions with poly(A binding proteins, ribosomal protein P0 and, in the case of Alba3, the cap-binding protein eIF4E4. In addition, Alba2 and Alba3 partially cosediment with polyribosomes in sucrose gradients. Alba-domain proteins seem to have exhibited great functional plasticity in the course of evolution. First identified as DNA-binding proteins in Archaea, then in association with nuclear RNase MRP/P in yeast and mammalian cells, they were recently described as components of a translationally silent complex containing stage-regulated mRNAs in Plasmodium. Our results are

Can infrared spectroscopy provide information on protein-protein interactions?

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Haris, Parvez I

2010-08-01

For most biophysical techniques, characterization of protein-protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600-1700 cm(-1)) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with (13)C or (13)C,(15)N has been introduced as a solution to this problem, enabling the study of protein-protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm(-1) towards lower frequency) upon (13)C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein-protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein-protein interactions are provided.

Alignment of non-covalent interactions at protein-protein interfaces.

Directory of Open Access Journals (Sweden)

Hongbo Zhu

Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.

Cell type-specific recruitment of Drosophila Lin-7 to distinct MAGUK-based protein complexes defines novel roles for Sdt and Dlg-S97.

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Bachmann, André; Timmer, Marco; Sierralta, Jimena; Pietrini, Grazia; Gundelfinger, Eckart D; Knust, Elisabeth; Thomas, Ulrich

2004-04-15

Stardust (Sdt) and Discs-Large (Dlg) are membrane-associated guanylate kinases (MAGUKs) involved in the organization of supramolecular protein complexes at distinct epithelial membrane compartments in Drosophila. Loss of either Sdt or Dlg affects epithelial development with severe effects on apico-basal polarity. Moreover, Dlg is required for the structural and functional integrity of synaptic junctions. Recent biochemical and cell culture studies have revealed that various mammalian MAGUKs can interact with mLin-7/Veli/MALS, a small PDZ-domain protein. To substantiate these findings for their in vivo significance with regard to Sdt- and Dlg-based protein complexes, we analyzed the subcellular distribution of Drosophila Lin-7 (DLin-7) and performed genetic and biochemical assays to characterize its interaction with either of the two MAGUKs. In epithelia, Sdt mediates the recruitment of DLin-7 to the subapical region, while at larval neuromuscular junctions, a particular isoform of Dlg, Dlg-S97, is required for postsynaptic localization of DLin-7. Ectopic expression of Dlg-S97 in epithelia, however, was not sufficient to induce a redistribution of DLin-7. These results imply that the recruitment of DLin-7 to MAGUK-based protein complexes is defined by cell-type specific mechanisms and that DLin-7 acts downstream of Sdt in epithelia and downstream of Dlg at synapses.

Biospecific protein immobilization for rapid analysis of weak protein interactions using self-interaction nanoparticle spectroscopy.

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Bengali, Aditya N; Tessier, Peter M

2009-10-01

"Reversible" protein interactions govern diverse biological behavior ranging from intracellular transport and toxic protein aggregation to protein crystallization and inactivation of protein therapeutics. Much less is known about weak protein interactions than their stronger counterparts since they are difficult to characterize, especially in a parallel format (in contrast to a sequential format) necessary for high-throughput screening. We have recently introduced a highly efficient approach of characterizing protein self-association, namely self-interaction nanoparticle spectroscopy (SINS; Tessier et al., 2008; J Am Chem Soc 130:3106-3112). This approach exploits the separation-dependent optical properties of gold nanoparticles to detect weak self-interactions between proteins immobilized on nanoparticles. A limitation of our previous work is that differences in the sequence and structure of proteins can lead to significant differences in their affinity to adsorb to nanoparticle surfaces, which complicates analysis of the corresponding protein self-association behavior. In this work we demonstrate a highly specific approach for coating nanoparticles with proteins using biotin-avidin interactions to generate protein-nanoparticle conjugates that report protein self-interactions through changes in their optical properties. Using lysozyme as a model protein that is refractory to characterization by conventional SINS, we demonstrate that surface Plasmon wavelengths for gold-avidin-lysozyme conjugates over a range of solution conditions (i.e., pH and ionic strength) are well correlated with lysozyme osmotic second virial coefficient measurements. Since SINS requires orders of magnitude less protein and time than conventional methods (e.g., static light scattering), we envision this approach will find application in large screens of protein self-association aimed at either preventing (e.g., protein aggregation) or promoting (e.g., protein crystallization) these

Selection of peptides interfering with protein-protein interaction.

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Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

2009-01-01

Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

Yeast Interacting Proteins Database: YLR447C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp...; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act

Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

Directory of Open Access Journals (Sweden)

Wuchty Stefan

2006-05-01

Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

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Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

Protein-protein interactions and cancer: targeting the central dogma.

Science.gov (United States)

Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

A conserved mammalian protein interaction network.

Directory of Open Access Journals (Sweden)

Åsa Pérez-Bercoff

Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Allele-Selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-Coding and Noncoding RNAs, and RNA Isoforms.

Directory of Open Access Journals (Sweden)

Roshan Mascarenhas

Full Text Available mRNA translation into proteins is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs, and genetic variants remains poorly understood. mRNA levels on polysomes have been shown to correlate well with expressed protein levels, pointing to polysomal loading as a critical factor. To study regulation and genetic factors of protein translation we measured levels and allelic ratios of mRNAs and ncRNAs (including microRNAs in lymphoblast cell lines (LCL and in polysomal fractions. We first used targeted assays to measure polysomal loading of mRNA alleles, confirming reported genetic effects on translation of OPRM1 and NAT1, and detecting no effect of rs1045642 (3435C>T in ABCB1 (MDR1 on polysomal loading while supporting previous results showing increased mRNA turnover of the 3435T allele. Use of high-throughput sequencing of complete transcript profiles (RNA-Seq in three LCLs revealed significant differences in polysomal loading of individual RNA classes and isoforms. Correlated polysomal distribution between protein-coding and non-coding RNAs suggests interactions between them. Allele-selective polysome recruitment revealed strong genetic influence for multiple RNAs, attributable either to differential expression of RNA isoforms or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Genes identified by different allelic RNA ratios between cytosol and polysomes were enriched with published expression quantitative trait loci (eQTLs affecting RNA functions, and associations with clinical phenotypes. Polysomal RNA-Seq combined with allelic ratio analysis provides a powerful approach to study polysomal RNA recruitment and regulatory variants affecting protein translation.

Interactive protein manipulation

International Nuclear Information System (INIS)

2003-01-01

We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures

Quality control methodology for high-throughput protein-protein interaction screening.

Science.gov (United States)

Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

Structural Bioinformatics and Protein Docking Analysis of the Molecular Chaperone-Kinase Interactions: Towards Allosteric Inhibition of Protein Kinases by Targeting the Hsp90-Cdc37 Chaperone Machinery

Directory of Open Access Journals (Sweden)

Gennady Verkhivker

2013-11-01

Full Text Available A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4 kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional “molecular brakes” that can lock (or unlock kinase from the system during client loading (release stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

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Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Physical interaction between replication protein A (RPA) and MRN: involvement of RPA2 phosphorylation and the N-terminus of RPA1.

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Oakley, Greg G; Tillison, Kristin; Opiyo, Stephen A; Glanzer, Jason G; Horn, Jeffrey M; Patrick, Steve M

2009-08-11

Replication protein A (RPA) is a heterotrimeric protein consisting of RPA1, RPA2, and RPA3 subunits that binds to single-stranded DNA (ssDNA) with high affinity. The response to replication stress requires the recruitment of RPA and the MRE11-RAD50-NBS1 (MRN) complex. RPA bound to ssDNA stabilizes stalled replication forks by recruiting checkpoint proteins involved in fork stabilization. MRN can bind DNA structures encountered at stalled or collapsed replication forks, such as ssDNA-double-stranded DNA (dsDNA) junctions or breaks, and promote the restart of DNA replication. Here, we demonstrate that RPA2 phosphorylation regulates the assembly of DNA damage-induced RPA and MRN foci. Using purified proteins, we observe a direct interaction between RPA with both NBS1 and MRE11. By utilizing RPA bound to ssDNA, we demonstrate that substituting RPA with phosphorylated RPA or a phosphomimetic weakens the interaction with the MRN complex. Also, the N-terminus of RPA1 is a critical component of the RPA-MRN protein-protein interaction. Deletion of the N-terminal oligonucleotide-oligosaccharide binding fold (OB-fold) of RPA1 abrogates interactions of RPA with MRN and individual proteins of the MRN complex. Further identification of residues critical for MRN binding in the N-terminus of RPA1 shows that substitution of Arg31 and Arg41 with alanines disrupts the RPA-MRN interaction and alters cell cycle progression in response to DNA damage. Thus, the N-terminus of RPA1 and phosphorylation of RPA2 regulate RPA-MRN interactions and are important in the response to DNA damage.

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

Directory of Open Access Journals (Sweden)

Vincent Vagenende

Full Text Available Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Yeast Interacting Proteins Database: YGR013W, YKL012W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tion U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the formation of the second commitm... PRP40 U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the form...ation of the second commitment complex Rows with this prey as prey (1) Rows with

A credit-card library approach for disrupting protein-protein interactions.

Science.gov (United States)

Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

2006-04-15

Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

Molecular tweezers modulate 14-3-3 protein-protein interactions

Science.gov (United States)

Bier, David; Rose, Rolf; Bravo-Rodriguez, Kenny; Bartel, Maria; Ramirez-Anguita, Juan Manuel; Dutt, Som; Wilch, Constanze; Klärner, Frank-Gerrit; Sanchez-Garcia, Elsa; Schrader, Thomas; Ottmann, Christian

2013-03-01

Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins—a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)—in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions.

Potential impact of climate-related changes is buffered by differential responses to recruitment and interactions

KAUST Repository

Menge, Bruce A.

2011-08-01

Detection of ecosystem responsiveness to climatic perturbations can provide insight into climate change consequences. Recent analyses linking phytoplankton abundance and mussel recruitment to the North Pacific Gyre Oscillation (NPGO) revealed a paradox. Despite large increases in mussel recruitment beginning in 2000, adult mussel responses were idiosyncratic by site and intertidal zone, with no response at one long-term site, and increases in the low zone (1.5% per year) and decreases in the mid zone (1.3% per year) at the other. What are the mechanisms underlying these differential changes? Species interactions such as facilitation by barnacles and predation are potential determinants of successful mussel colonization. To evaluate these effects, we analyzed patterns of barnacle recruitment, determined if predation rate covaried with the increase in mussel recruitment, and tested facilitation interactions in a field experiment. Neither magnitude nor season of barnacle recruitment changed meaningfully with site or zone from the 1990s to the 2000s. In contrast to the relationship between NPGO and local-scale mussel recruitment, relationships between local-scale patterns of barnacle recruitment and climate indices were weak. Despite differences in rates of prey recruitment and abundance of sea stars in 1990–1991, 1999–2000, and 2007–2008, predation rates were nearly identical in experiments before, during, and after 1999–2000. The facilitation experiment showed that mussels M. trossulus only became abundant when barnacle recruitment was allowed, when abundance of barnacles reached high abundance of ∼50% cover, and when mussel recruitment was sufficiently high. Thus, in the low zone minimal changes in mussel abundance despite sharply increased recruitment rates are consistent with the hypothesis that change in adult mussel cover was buffered by the relative insensitivity of barnacle recruitment to climatic fluctuations, and a resultant lack of change in

Potential impact of climate-related changes is buffered by differential responses to recruitment and interactions

KAUST Repository

Menge, Bruce A.; Hacker, Sally D.; Freidenburg, Tess; Lubchenco, Jane; Craig, Ryan; Rilov, Gil; Noble, Mae Marjore; Richmond, Erin

2011-01-01

Detection of ecosystem responsiveness to climatic perturbations can provide insight into climate change consequences. Recent analyses linking phytoplankton abundance and mussel recruitment to the North Pacific Gyre Oscillation (NPGO) revealed a paradox. Despite large increases in mussel recruitment beginning in 2000, adult mussel responses were idiosyncratic by site and intertidal zone, with no response at one long-term site, and increases in the low zone (1.5% per year) and decreases in the mid zone (1.3% per year) at the other. What are the mechanisms underlying these differential changes? Species interactions such as facilitation by barnacles and predation are potential determinants of successful mussel colonization. To evaluate these effects, we analyzed patterns of barnacle recruitment, determined if predation rate covaried with the increase in mussel recruitment, and tested facilitation interactions in a field experiment. Neither magnitude nor season of barnacle recruitment changed meaningfully with site or zone from the 1990s to the 2000s. In contrast to the relationship between NPGO and local-scale mussel recruitment, relationships between local-scale patterns of barnacle recruitment and climate indices were weak. Despite differences in rates of prey recruitment and abundance of sea stars in 1990–1991, 1999–2000, and 2007–2008, predation rates were nearly identical in experiments before, during, and after 1999–2000. The facilitation experiment showed that mussels M. trossulus only became abundant when barnacle recruitment was allowed, when abundance of barnacles reached high abundance of ∼50% cover, and when mussel recruitment was sufficiently high. Thus, in the low zone minimal changes in mussel abundance despite sharply increased recruitment rates are consistent with the hypothesis that change in adult mussel cover was buffered by the relative insensitivity of barnacle recruitment to climatic fluctuations, and a resultant lack of change in

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are

Interactive protein manipulation

Energy Technology Data Exchange (ETDEWEB)

SNCrivelli@lbl.gov

2003-07-01

We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures.

[Detection of protein-protein interactions by FRET and BRET methods].

Science.gov (United States)

Matoulková, E; Vojtěšek, B

2014-01-01

Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

Yeast Interacting Proteins Database: YGL237C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote... expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein

Yeast Interacting Proteins Database: YKL002W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote...xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp

Direct interactions of the five known Fanconi anaemia proteins suggest a common functional pathway.

Science.gov (United States)

Medhurst, A L; Huber, P A; Waisfisz, Q; de Winter , J P; Mathew, C G

2001-02-15

Fanconi anaemia (FA) is an autosomal recessive inherited disorder associated with a progressive aplastic anaemia, diverse congenital abnormalities and cancer. The condition is genetically heterogeneous, with at least seven complementation groups (A-G) described. Cells from individuals who are homozygous for mutations in FA genes are characterized by chromosomal instability and hypersensitivity to DNA interstrand crosslinking agents. These features suggest a possible role for the encoded proteins in the recognition or repair of these lesions, but neither their function nor whether they operate in a concerted or discrete functional pathways is known. The recent cloning of the FANCF and FANCE genes has allowed us to investigate the interaction of the proteins encoded by five of the seven complementation groups of FA. We used the yeast two-hybrid system and co-immunoprecipitation analysis to test the 10 possible pairs of proteins for direct interaction. In addition to the previously described binding of FANCA to FANCG, we now demonstrate direct interaction of FANCF with FANCG, of FANCC with FANCE and a weaker interaction of FANCE with both FANCA and FANCG. These findings show that the newly identified FANCE protein is an integral part of the FA pathway, and support the concept of a functional link between all known proteins encoded by the genes that are mutated in this disorder. These proteins may act either as a multimeric complex or by sequential recruitment of subsets of the proteins in a common pathway that protects the genomic integrity of mammalian cells.

A scored human protein-protein interaction network to catalyze genomic interpretation

DEFF Research Database (Denmark)

Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

2017-01-01

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

Protein function prediction using neighbor relativity in protein-protein interaction network.

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Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

International Nuclear Information System (INIS)

Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

2011-01-01

The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations

HIV-1 tat protein recruits CIS to the cytoplasmic tail of CD127 to induce receptor ubiquitination and proteasomal degradation

Energy Technology Data Exchange (ETDEWEB)

Sugden, Scott, E-mail: scott.sugden@ircm.qc.ca [The Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6 (Canada); Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, Canada K1H 8M5 (Canada); Ghazawi, Feras [The Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6 (Canada); Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, Canada K1H 8M5 (Canada); MacPherson, Paul, E-mail: pmacpherson@toh.on.ca [The Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6 (Canada); Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, Canada K1H 8M5 (Canada); Division of Infectious Diseases, The Ottawa Hospital General Campus, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6 (Canada)

2016-11-15

HIV-1 Tat protein down regulates expression of the IL-7 receptor alpha-chain (CD127) from the surface of CD8 T cells resulting in impaired T cell proliferation and cytolytic capacity. We have previously shown that soluble Tat protein is taken up by CD8 T cells and interacts with the cytoplasmic tail of CD127 to induce receptor degradation. The N-terminal domain of Tat interacts with CD127 while the basic domain directs CD127 to the proteasome. We have also shown that upon IL-7 binding to its receptor, CD127 is phosphorylated resulting in CIS-mediated proteasomal degradation. Here, we show that Tat mimics this process by recruiting CIS to CD127 in the absence of IL-7 and receptor phosphorylation, leading to CD127 ubiquitination and degradation. Tat therefore acts as an adapter to induce cellular responses under conditions where they may not otherwise occur. Thusly, Tat reduces IL-7 signaling and impairs CD8 T cell survival and function. -- Highlights: •Soluble HIV-1 Tat decreases CD127 expression on CD8 T cells, causing dysfunction. •Tat induces CD127 ubiquitination without activating IL-7 signaling. •Tat binds CD127 and recruits the E3 ubiquitin ligase CIS via its basic domain. •Tat hijacks a normal cellular mechanism to degrade CD127 without IL-7 signaling.

HIV-1 tat protein recruits CIS to the cytoplasmic tail of CD127 to induce receptor ubiquitination and proteasomal degradation

International Nuclear Information System (INIS)

Sugden, Scott; Ghazawi, Feras; MacPherson, Paul

2016-01-01

HIV-1 Tat protein down regulates expression of the IL-7 receptor alpha-chain (CD127) from the surface of CD8 T cells resulting in impaired T cell proliferation and cytolytic capacity. We have previously shown that soluble Tat protein is taken up by CD8 T cells and interacts with the cytoplasmic tail of CD127 to induce receptor degradation. The N-terminal domain of Tat interacts with CD127 while the basic domain directs CD127 to the proteasome. We have also shown that upon IL-7 binding to its receptor, CD127 is phosphorylated resulting in CIS-mediated proteasomal degradation. Here, we show that Tat mimics this process by recruiting CIS to CD127 in the absence of IL-7 and receptor phosphorylation, leading to CD127 ubiquitination and degradation. Tat therefore acts as an adapter to induce cellular responses under conditions where they may not otherwise occur. Thusly, Tat reduces IL-7 signaling and impairs CD8 T cell survival and function. -- Highlights: •Soluble HIV-1 Tat decreases CD127 expression on CD8 T cells, causing dysfunction. •Tat induces CD127 ubiquitination without activating IL-7 signaling. •Tat binds CD127 and recruits the E3 ubiquitin ligase CIS via its basic domain. •Tat hijacks a normal cellular mechanism to degrade CD127 without IL-7 signaling.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

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He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Mass spectrometric analysis of protein interactions

DEFF Research Database (Denmark)

Borch, Jonas; Jørgensen, Thomas J. D.; Roepstorff, Peter

2005-01-01

Mass spectrometry is a powerful tool for identification of interaction partners and structural characterization of protein interactions because of its high sensitivity, mass accuracy and tolerance towards sample heterogeneity. Several tools that allow studies of protein interaction are now...... available and recent developments that increase the confidence of studies of protein interaction by mass spectrometry include quantification of affinity-purified proteins by stable isotope labeling and reagents for surface topology studies that can be identified by mass-contributing reporters (e.g. isotope...... labels, cleavable cross-linkers or fragment ions. The use of mass spectrometers to study protein interactions using deuterium exchange and for analysis of intact protein complexes recently has progressed considerably....

Evolutionary diversification of protein-protein interactions by interface add-ons.

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Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

2017-10-03

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Inferring high-confidence human protein-protein interactions

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Yu Xueping

2012-05-01

Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

Direct Binding to Replication Protein A (RPA)-coated Single-stranded DNA Allows Recruitment of the ATR Activator TopBP1 to Sites of DNA Damage*

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Acevedo, Julyana; Yan, Shan; Michael, W. Matthew

2016-01-01

A critical event for the ability of cells to tolerate DNA damage and replication stress is activation of the ATR kinase. ATR activation is dependent on the BRCT (BRCA1 C terminus) repeat-containing protein TopBP1. Previous work has shown that recruitment of TopBP1 to sites of DNA damage and stalled replication forks is necessary for downstream events in ATR activation; however, the mechanism for this recruitment was not known. Here, we use protein binding assays and functional studies in Xenopus egg extracts to show that TopBP1 makes a direct interaction, via its BRCT2 domain, with RPA-coated single-stranded DNA. We identify a point mutant that abrogates this interaction and show that this mutant fails to accumulate at sites of DNA damage and that the mutant cannot activate ATR. These data thus supply a mechanism for how the critical ATR activator, TopBP1, senses DNA damage and stalled replication forks to initiate assembly of checkpoint signaling complexes. PMID:27129245

Yeast Interacting Proteins Database: YPR103W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors...gulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf

Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology.

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DeBlasio, Stacy L; Chavez, Juan D; Alexander, Mariko M; Ramsey, John; Eng, Jimmy K; Mahoney, Jaclyn; Gray, Stewart M; Bruce, James E; Cilia, Michelle

2016-02-15

Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection-hallmarks of host-pathogen interactions-were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

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Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

Temperature, precipitation and biotic interactions as determinants of tree seedling recruitment across the tree line ecotone.

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Tingstad, Lise; Olsen, Siri Lie; Klanderud, Kari; Vandvik, Vigdis; Ohlson, Mikael

2015-10-01

Seedling recruitment is a critical life history stage for trees, and successful recruitment is tightly linked to both abiotic factors and biotic interactions. In order to better understand how tree species' distributions may change in response to anticipated climate change, more knowledge of the effects of complex climate and biotic interactions is needed. We conducted a seed-sowing experiment to investigate how temperature, precipitation and biotic interactions impact recruitment of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) seedlings in southern Norway. Seeds were sown into intact vegetation and experimentally created gaps. To study the combined effects of temperature and precipitation, the experiment was replicated across 12 sites, spanning a natural climate gradient from boreal to alpine and from sub-continental to oceanic. Seedling emergence and survival were assessed 12 and 16 months after sowing, respectively, and above-ground biomass and height were determined at the end of the experiment. Interestingly, very few seedlings were detected in the boreal sites, and the highest number of seedlings emerged and established in the alpine sites, indicating that low temperature did not limit seedling recruitment. Site precipitation had an overall positive effect on seedling recruitment, especially at intermediate precipitation levels. Seedling emergence, establishment and biomass were higher in gap plots compared to intact vegetation at all temperature levels. These results suggest that biotic interactions in the form of competition may be more important than temperature as a limiting factor for tree seedling recruitment in the sub- and low-alpine zone of southern Norway.

Human T-cell leukemia virus type 1 Tax requires direct access to DNA for recruitment of CREB binding protein to the viral promoter.

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Lenzmeier, B A; Giebler, H A; Nyborg, J K

1998-02-01

Efficient human T-cell leukemia virus type 1 (HTLV-1) replication and viral gene expression are dependent upon the virally encoded oncoprotein Tax. To activate HTLV-1 transcription, Tax interacts with the cellular DNA binding protein cyclic AMP-responsive element binding protein (CREB) and recruits the coactivator CREB binding protein (CBP), forming a nucleoprotein complex on the three viral cyclic AMP-responsive elements (CREs) in the HTLV-1 promoter. Short stretches of dG-dC-rich (GC-rich) DNA, immediately flanking each of the viral CREs, are essential for Tax recruitment of CBP in vitro and Tax transactivation in vivo. Although the importance of the viral CRE-flanking sequences is well established, several studies have failed to identify an interaction between Tax and the DNA. The mechanistic role of the viral CRE-flanking sequences has therefore remained enigmatic. In this study, we used high resolution methidiumpropyl-EDTA iron(II) footprinting to show that Tax extended the CREB footprint into the GC-rich DNA flanking sequences of the viral CRE. The Tax-CREB footprint was enhanced but not extended by the KIX domain of CBP, suggesting that the coactivator increased the stability of the nucleoprotein complex. Conversely, the footprint pattern of CREB on a cellular CRE lacking GC-rich flanking sequences did not change in the presence of Tax or Tax plus KIX. The minor-groove DNA binding drug chromomycin A3 bound to the GC-rich flanking sequences and inhibited the association of Tax and the Tax-CBP complex without affecting CREB binding. Tax specifically cross-linked to the viral CRE in the 5'-flanking sequence, and this cross-link was blocked by chromomycin A3. Together, these data support a model where Tax interacts directly with both CREB and the minor-groove viral CRE-flanking sequences to form a high-affinity binding site for the recruitment of CBP to the HTLV-1 promoter.

Water-Protein Interactions: The Secret of Protein Dynamics

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Silvia Martini

2013-01-01

Full Text Available Water-protein interactions help to maintain flexible conformation conditions which are required for multifunctional protein recognition processes. The intimate relationship between the protein surface and hydration water can be analyzed by studying experimental water properties measured in protein systems in solution. In particular, proteins in solution modify the structure and the dynamics of the bulk water at the solute-solvent interface. The ordering effects of proteins on hydration water are extended for several angstroms. In this paper we propose a method for analyzing the dynamical properties of the water molecules present in the hydration shells of proteins. The approach is based on the analysis of the effects of protein-solvent interactions on water protons NMR relaxation parameters. NMR relaxation parameters, especially the nonselective (R1NS and selective (R1SE spin-lattice relaxation rates of water protons, are useful for investigating the solvent dynamics at the macromolecule-solvent interfaces as well as the perturbation effects caused by the water-macromolecule interactions on the solvent dynamical properties. In this paper we demonstrate that Nuclear Magnetic Resonance Spectroscopy can be used to determine the dynamical contributions of proteins to the water molecules belonging to their hydration shells.

Protein-protein interactions in the regulation of WRKY transcription factors.

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Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

IQGAP1 is a novel CXCR2-interacting protein and essential component of the "chemosynapse".

Directory of Open Access Journals (Sweden)

Nicole F Neel

Full Text Available Chemotaxis is essential for a number of physiological processes including leukocyte recruitment. Chemokines initiate intracellular signaling pathways necessary for chemotaxis through binding seven transmembrane G protein-couple receptors. Little is known about the proteins that interact with the intracellular domains of chemokine receptors to initiate cellular signaling upon ligand binding. CXCR2 is a major chemokine receptor expressed on several cell types, including endothelial cells and neutrophils. We hypothesize that multiple proteins interact with the intracellular domains of CXCR2 upon ligand stimulation and these interactions comprise a "chemosynapse", and play important roles in transducing CXCR2 mediated signaling processes.In an effort to define the complex of proteins that assemble upon CXCR2 activation to relay signals from activated chemokine receptors, a proteomics approach was employed to identify proteins that co-associate with CXCR2 with or without ligand stimulation. The components of the CXCR2 "chemosynapse" are involved in processes ranging from intracellular trafficking to cytoskeletal modification. IQ motif containing GTPase activating protein 1 (IQGAP1 was among the novel proteins identified to interact directly with CXCR2. Herein, we demonstrate that CXCR2 co-localizes with IQGAP1 at the leading edge of polarized human neutrophils and CXCR2 expressing differentiated HL-60 cells. Moreover, amino acids 1-160 of IQGAP1 directly interact with the carboxyl-terminal domain of CXCR2 and stimulation with CXCL8 enhances IQGAP1 association with Cdc42.Our studies indicate that IQGAP1 is a novel essential component of the CXCR2 "chemosynapse".

The Transcriptional Repressive Activity of KRAB Zinc Finger Proteins Does Not Correlate with Their Ability to Recruit TRIM28.

Directory of Open Access Journals (Sweden)

Kristin E Murphy

Full Text Available KRAB domain Zinc finger proteins are one of the most abundant families of transcriptional regulators in higher vertebrates. The prevailing view is that KRAB domain proteins function as potent transcriptional repressors by recruiting TRIM28 and promoting heterochromatin spreading. However, the extent to which all KRAB domain proteins are TRIM28-dependent transcriptional repressors is currently unclear. Our studies on mouse ZFP568 revealed that TRIM28 recruitment by KRAB domain proteins is not sufficient to warrant transcriptional repressive activity. By using luciferase reporter assays and yeast two-hybrid experiments, we tested the ability of ZFP568 and other mouse KRAB domain proteins to repress transcription and bind TRIM28. We found that some mouse KRAB domain proteins are poor transcriptional repressors despite their ability to recruit TRIM28, while others showed strong KRAB-dependent transcriptional repression, but no TRIM28 binding. Together, our results show that the transcriptional repressive activity of KRAB-ZNF proteins does not correlate with their ability to recruit TRIM28, and provide evidence that KRAB domains can regulate transcription in a TRIM28-independent fashion. Our findings challenge the current understanding of the molecular mechanisms used by KRAB domain proteins to control gene expression and highlight that a high percentage of KRAB domain proteins in the mouse genome differ from the consensus KRAB sequence at amino acid residues that are critical for TRIM28 binding and/or repressive activity.

Yeast Interacting Proteins Database: YMR280C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available olved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensor... glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, an

Protein-Protein Interaction Databases

DEFF Research Database (Denmark)

Szklarczyk, Damian; Jensen, Lars Juhl

2015-01-01

Years of meticulous curation of scientific literature and increasingly reliable computational predictions have resulted in creation of vast databases of protein interaction data. Over the years, these repositories have become a basic framework in which experiments are analyzed and new directions...

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

Science.gov (United States)

Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Distinct modes of recruitment of the CCR4-NOT complex by Drosophila and vertebrate Nanos.

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Raisch, Tobias; Bhandari, Dipankar; Sabath, Kevin; Helms, Sigrun; Valkov, Eugene; Weichenrieder, Oliver; Izaurralde, Elisa

2016-05-02

Nanos proteins repress the expression of target mRNAs by recruiting effector complexes through non-conserved N-terminal regions. In vertebrates, Nanos proteins interact with the NOT1 subunit of the CCR4-NOT effector complex through a NOT1 interacting motif (NIM), which is absent in Nanos orthologs from several invertebrate species. Therefore, it has remained unclear whether the Nanos repressive mechanism is conserved and whether it also involves direct interactions with the CCR4-NOT deadenylase complex in invertebrates. Here, we identify an effector domain (NED) that is necessary for the Drosophila melanogaster (Dm) Nanos to repress mRNA targets. The NED recruits the CCR4-NOT complex through multiple and redundant binding sites, including a central region that interacts with the NOT module, which comprises the C-terminal domains of NOT1-3. The crystal structure of the NED central region bound to the NOT module reveals an unanticipated bipartite binding interface that contacts NOT1 and NOT3 and is distinct from the NIM of vertebrate Nanos. Thus, despite the absence of sequence conservation, the N-terminal regions of Nanos proteins recruit CCR4-NOT to assemble analogous repressive complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

The Arabidopsis GAGA-Binding Factor BASIC PENTACYSTEINE6 Recruits the POLYCOMB-REPRESSIVE COMPLEX1 Component LIKE HETEROCHROMATIN PROTEIN1 to GAGA DNA Motifs.

Science.gov (United States)

Hecker, Andreas; Brand, Luise H; Peter, Sébastien; Simoncello, Nathalie; Kilian, Joachim; Harter, Klaus; Gaudin, Valérie; Wanke, Dierk

2015-07-01

Polycomb-repressive complexes (PRCs) play key roles in development by repressing a large number of genes involved in various functions. Much, however, remains to be discovered about PRC-silencing mechanisms as well as their targeting to specific genomic regions. Besides other mechanisms, GAGA-binding factors in animals can guide PRC members in a sequence-specific manner to Polycomb-responsive DNA elements. Here, we show that the Arabidopsis (Arabidopsis thaliana) GAGA-motif binding factor protein basic pentacysteine6 (BPC6) interacts with like heterochromatin protein1 (LHP1), a PRC1 component, and associates with vernalization2 (VRN2), a PRC2 component, in vivo. By using a modified DNA-protein interaction enzyme-linked immunosorbant assay, we could show that BPC6 was required and sufficient to recruit LHP1 to GAGA motif-containing DNA probes in vitro. We also found that LHP1 interacts with VRN2 and, therefore, can function as a possible scaffold between BPC6 and VRN2. The lhp1-4 bpc4 bpc6 triple mutant displayed a pleiotropic phenotype, extreme dwarfism and early flowering, which disclosed synergistic functions of LHP1 and group II plant BPC members. Transcriptome analyses supported this synergy and suggested a possible function in the concerted repression of homeotic genes, probably through histone H3 lysine-27 trimethylation. Hence, our findings suggest striking similarities between animal and plant GAGA-binding factors in the recruitment of PRC1 and PRC2 components to Polycomb-responsive DNA element-like GAGA motifs, which must have evolved through convergent evolution. © 2015 American Society of Plant Biologists. All Rights Reserved.

PSAIA – Protein Structure and Interaction Analyzer

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Vlahoviček Kristian

2008-04-01

Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

Scoring functions for protein-protein interactions.

Science.gov (United States)

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

The role of electrostatics in protein-protein interactions of a monoclonal antibody.

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Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R

2014-07-07

Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.

Detecting protein-protein interactions in living cells

DEFF Research Database (Denmark)

Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche

2009-01-01

to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C......-terminal of the NMDA receptor and PDZ2 of PSD-95 were fused to green fluorescent protein (GFP) and Renilla luciferase (Rluc) and expressed in COS7 cells. A robust and specific BRET signal was obtained by expression of the appropriate partner proteins and subsequently, the assay was used to evaluate a Tat......The PDZ domain mediated interaction between the NMDA receptor and its intracellular scaffolding protein, PSD-95, is a potential target for treatment of ischemic brain diseases. We have recently developed a number of peptide analogues with improved affinity for the PDZ domains of PSD-95 compared...

Globular and disordered – the non-identical twins in protein-protein interactions

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Kaare eTeilum

2015-07-01

Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.

Emergence of modularity and disassortativity in protein-protein interaction networks.

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Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

2010-12-01

In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

Dendrimer-protein interactions versus dendrimer-based nanomedicine.

Science.gov (United States)

Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

2017-04-01

Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Towards a map of the Populus biomass protein-protein interaction network

Energy Technology Data Exchange (ETDEWEB)

Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2015-07-31

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in

Globular and disordered-the non-identical twins in protein-protein interactions

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt

2015-01-01

as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

Targeting protein-protein interactions for parasite control.

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Christina M Taylor

2011-04-01

Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

Science.gov (United States)

Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Protein complex prediction based on k-connected subgraphs in protein interaction network

OpenAIRE

Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

2010-01-01

Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

Potential disruption of protein-protein interactions by graphene oxide

International Nuclear Information System (INIS)

Feng, Mei; Kang, Hongsuk; Luan, Binquan; Yang, Zaixing; Zhou, Ruhong

2016-01-01

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide

Energy Technology Data Exchange (ETDEWEB)

Feng, Mei [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Kang, Hongsuk; Luan, Binquan [Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Yang, Zaixing [Institute of Quantitative Biology and Medicine, SRMP and RAD-X, and Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou 215123 (China); Zhou, Ruhong, E-mail: ruhong@us.ibm.com [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Department of Chemistry, Columbia University, New York, New York 10027 (United States)

2016-06-14

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

Science.gov (United States)

Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

2015-12-01

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Interaction between M-like protein and macrophage thioredoxin facilitates antiphagocytosis for Streptococcus equi ssp. zooepidemicus.

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Zhe Ma

Full Text Available Streptococcus equi ssp. zooepidemicus (S. zooepidemicus, S.z is one of the common pathogens that can cause septicemia, meningitis, and mammitis in domesticated species. M-like protein (SzP is an important virulence factor of S. zooepidemicus and contributes to bacterial infection and antiphagocytosis. The interaction between SzP of S. zooepidemicus and porcine thioredoxin (TRX was identified by the yeast two-hybrid and further confirmed by co-immunoprecipitation. SzP interacted with both reduced and the oxidized forms of TRX without inhibiting TRX activity. Membrane anchored SzP was able to recruit TRX to the surface, which would facilitate the antiphagocytosis of the bacteria. Further experiments revealed that TRX regulated the alternative complement pathway by inhibiting C3 convertase activity and associating with factor H (FH. TRX alone inhibited C3 cleavage and C3a production, and the inhibitory effect was additive when FH was also present. TRX inhibited C3 deposition on the bacterial surface when it was recruited by SzP. These new findings indicated that S. zooepidemicus used SzP to recruit TRX and regulated the alternative complement pathways to evade the host immune phagocytosis.

Interaction between M-Like Protein and Macrophage Thioredoxin Facilitates Antiphagocytosis for Streptococcus equi ssp. zooepidemicus

Science.gov (United States)

Ma, Zhe; Zhang, Hui; Zheng, Junxi; Li, Yue; Yi, Li; Fan, Hongjie; Lu, Chengping

2012-01-01

Streptococcus equi ssp. zooepidemicus (S. zooepidemicus, S.z) is one of the common pathogens that can cause septicemia, meningitis, and mammitis in domesticated species. M-like protein (SzP) is an important virulence factor of S. zooepidemicus and contributes to bacterial infection and antiphagocytosis. The interaction between SzP of S. zooepidemicus and porcine thioredoxin (TRX) was identified by the yeast two-hybrid and further confirmed by co-immunoprecipitation. SzP interacted with both reduced and the oxidized forms of TRX without inhibiting TRX activity. Membrane anchored SzP was able to recruit TRX to the surface, which would facilitate the antiphagocytosis of the bacteria. Further experiments revealed that TRX regulated the alternative complement pathway by inhibiting C3 convertase activity and associating with factor H (FH). TRX alone inhibited C3 cleavage and C3a production, and the inhibitory effect was additive when FH was also present. TRX inhibited C3 deposition on the bacterial surface when it was recruited by SzP. These new findings indicated that S. zooepidemicus used SzP to recruit TRX and regulated the alternative complement pathways to evade the host immune phagocytosis. PMID:22384152

Building blocks for protein interaction devices

Science.gov (United States)

Grünberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis

2010-01-01

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them. PMID:20215443

Differential recruitment of DNA Ligase I and III to DNA repair sites

Science.gov (United States)

Mortusewicz, Oliver; Rothbauer, Ulrich; Cardoso, M. Cristina; Leonhardt, Heinrich

2006-01-01

DNA ligation is an essential step in DNA replication, repair and recombination. Mammalian cells contain three DNA Ligases that are not interchangeable although they use the same catalytic reaction mechanism. To compare the recruitment of the three eukaryotic DNA Ligases to repair sites in vivo we introduced DNA lesions in human cells by laser microirradiation. Time lapse microscopy of fluorescently tagged proteins showed that DNA Ligase III accumulated at microirradiated sites before DNA Ligase I, whereas we could detect only a faint accumulation of DNA Ligase IV. Recruitment of DNA Ligase I and III to repair sites was cell cycle independent. Mutational analysis and binding studies revealed that DNA Ligase I was recruited to DNA repair sites by interaction with PCNA while DNA Ligase III was recruited via its BRCT domain mediated interaction with XRCC1. Selective recruitment of specialized DNA Ligases may have evolved to accommodate the particular requirements of different repair pathways and may thus enhance efficiency of DNA repair. PMID:16855289

Analysis of intraviral protein-protein interactions of the SARS coronavirus ORFeome.

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Albrecht von Brunn

2007-05-01

Full Text Available The severe acute respiratory syndrome coronavirus (SARS-CoV genome is predicted to encode 14 functional open reading frames, leading to the expression of up to 30 structural and non-structural protein products. The functions of a large number of viral ORFs are poorly understood or unknown. In order to gain more insight into functions and modes of action and interaction of the different proteins, we cloned the viral ORFeome and performed a genome-wide analysis for intraviral protein interactions and for intracellular localization. 900 pairwise interactions were tested by yeast-two-hybrid matrix analysis, and more than 65 positive non-redundant interactions, including six self interactions, were identified. About 38% of interactions were subsequently confirmed by CoIP in mammalian cells. Nsp2, nsp8 and ORF9b showed a wide range of interactions with other viral proteins. Nsp8 interacts with replicase proteins nsp2, nsp5, nsp6, nsp7, nsp8, nsp9, nsp12, nsp13 and nsp14, indicating a crucial role as a major player within the replication complex machinery. It was shown by others that nsp8 is essential for viral replication in vitro, whereas nsp2 is not. We show that also accessory protein ORF9b does not play a pivotal role for viral replication, as it can be deleted from the virus displaying normal plaque sizes and growth characteristics in Vero cells. However, it can be expected to be important for the virus-host interplay and for pathogenicity, due to its large number of interactions, by enhancing the global stability of the SARS proteome network, or play some unrealized role in regulating protein-protein interactions. The interactions identified provide valuable material for future studies.

Specific interaction with cardiolipin triggers functional activation of Dynamin-Related Protein 1.

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Itsasne Bustillo-Zabalbeitia

Full Text Available Dynamin-Related Protein 1 (Drp1, a large GTPase of the dynamin superfamily, is required for mitochondrial fission in healthy and apoptotic cells. Drp1 activation is a complex process that involves translocation from the cytosol to the mitochondrial outer membrane (MOM and assembly into rings/spirals at the MOM, leading to membrane constriction/division. Similar to dynamins, Drp1 contains GTPase (G, bundle signaling element (BSE and stalk domains. However, instead of the lipid-interacting Pleckstrin Homology (PH domain present in the dynamins, Drp1 contains the so-called B insert or variable domain that has been suggested to play an important role in Drp1 regulation. Different proteins have been implicated in Drp1 recruitment to the MOM, although how MOM-localized Drp1 acquires its fully functional status remains poorly understood. We found that Drp1 can interact with pure lipid bilayers enriched in the mitochondrion-specific phospholipid cardiolipin (CL. Building on our previous study, we now explore the specificity and functional consequences of this interaction. We show that a four lysine module located within the B insert of Drp1 interacts preferentially with CL over other anionic lipids. This interaction dramatically enhances Drp1 oligomerization and assembly-stimulated GTP hydrolysis. Our results add significantly to a growing body of evidence indicating that CL is an important regulator of many essential mitochondrial functions.

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

Science.gov (United States)

Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Evidence for the interaction of the regulatory protein Ki-1/57 with p53 and its interacting proteins

International Nuclear Information System (INIS)

Nery, Flavia C.; Rui, Edmilson; Kuniyoshi, Tais M.; Kobarg, Joerg

2006-01-01

Ki-1/57 is a cytoplasmic and nuclear phospho-protein of 57 kDa and interacts with the adaptor protein RACK1, the transcription factor MEF2C, and the chromatin remodeling factor CHD3, suggesting that it might be involved in the regulation of transcription. Here, we describe yeast two-hybrid studies that identified a total of 11 proteins interacting with Ki-1/57, all of which interact or are functionally associated with p53 or other members of the p53 family of proteins. We further found that Ki-1/57 is able to interact with p53 itself in the yeast two-hybrid system when the interaction was tested directly. This interaction could be confirmed by pull down assays with purified proteins in vitro and by reciprocal co-immunoprecipitation assays from the human Hodgkin analogous lymphoma cell line L540. Furthermore, we found that the phosphorylation of p53 by PKC abolishes its interaction with Ki-1/57 in vitro

Proximity Ligation In situ Assay is a Powerful Tool to Monitor Specific ATG Protein Interactions following Autophagy Induction.

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Thierry Gauthier

Full Text Available Macroautophagy is a highly regulated intracellular degradation process which has been extensively studied over the last decade. This pathway has been initially described as a non selective process inducing the degradation of parts of the cytoplasm as well as organelles at random. Nevertheless, over the last few years, new research highlighted the existence of a more selective autophagy pathway specifically recruiting some organelles or aggregates to the autophagosomes in order to induce their degradation. These selective autophagy pathways such as aggrephagy, mitophagy, pexophagy or xenophagy, involve the intervention of a cargo, the material to be degraded, cargo adapters, the molecules allowing the recruitment of the cargo to the autophagosome, and the proteins of the ATG8 family which link the cargo adapters to the autophagosome. One of the main questions which now remain is to develop new techniques and protocols able to discriminate between these different types of induced autophagy. In our work, we studied the possibility to use the P-LISA technique, which has been recently developed to study endogenous in vivo protein interactions, as a new technique to characterize the ATG proteins specifically involved in bulk or selective autophagy. In this manuscript, we indeed demonstrate that this technique allows the study of endogenous ATG protein interactions in cells following autophagy induction, but more interestingly that this technique might be used to characterize the ATG proteins involved in selective autophagy.

Protein complex prediction based on k-connected subgraphs in protein interaction network

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Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

Molecular simulations of lipid-mediated protein-protein interactions

NARCIS (Netherlands)

de Meyer, F.J.M.; Venturoli, M.; Smit, B.

2008-01-01

Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the

Efficient extraction of protein-protein interactions from full-text articles.

Science.gov (United States)

Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

2010-01-01

Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

Recruitment of the major vault protein by InlK: a Listeria monocytogenes strategy to avoid autophagy.

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Laurent Dortet

2011-08-01

Full Text Available L. monocytogenes is a facultative intracellular bacterium responsible for listeriosis. It is able to invade, survive and replicate in phagocytic and non-phagocytic cells. The infectious process at the cellular level has been extensively studied and many virulence factors have been identified. Yet, the role of InlK, a member of the internalin family specific to L. monocytogenes, remains unknown. Here, we first show using deletion analysis and in vivo infection, that InlK is a bona fide virulence factor, poorly expressed in vitro and well expressed in vivo, and that it is anchored to the bacterial surface by sortase A. We then demonstrate by a yeast two hybrid screen using InlK as a bait, validated by pulldown experiments and immunofluorescence analysis that intracytosolic bacteria via an interaction with the protein InlK interact with the Major Vault Protein (MVP, the main component of cytoplasmic ribonucleoproteic particules named vaults. Although vaults have been implicated in several cellular processes, their role has remained elusive. Our analysis demonstrates that MVP recruitment disguises intracytosolic bacteria from autophagic recognition, leading to an increased survival rate of InlK over-expressing bacteria compared to InlK(- bacteria. Together these results reveal that MVP is hijacked by L. monocytogenes in order to counteract the autophagy process, a finding that could have major implications in deciphering the cellular role of vault particles.

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

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Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

An analysis pipeline for the inference of protein-protein interaction networks

Energy Technology Data Exchange (ETDEWEB)

Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

2009-12-01

An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

Receptor activity-independent recruitment of βarrestin2 reveals specific signalling modes

Science.gov (United States)

Terrillon, Sonia; Bouvier, Michel

2004-01-01

The roles of βarrestins in regulating G protein coupling and receptor endocytosis following agonist stimulation of G protein-coupled receptors are well characterised. However, their ability to act on their own as direct modulators or activators of signalling remains poorly characterised. Here, βarrestin2 intrinsic signalling properties were assessed by forcing the recruitment of this accessory protein to vasopressin V1a or V2 receptors independently of agonist-promoted activation of the receptors. Such induction of a stable interaction with βarrestin2 initiated receptor endocytosis leading to intracellular accumulation of the βarrestin/receptor complexes. Interestingly, βarrestin2 association to a single receptor protomer was sufficient to elicit receptor dimer internalisation. In addition to recapitulating βarrestin2 classical actions on receptor trafficking, the receptor activity-independent recruitment of βarrestin2 activated the extracellular signal-regulated kinases. In the latter case, recruitment to the receptor itself was not required since kinase activation could be mediated by βarrestin2 translocation to the plasma membrane in the absence of any interacting receptor. These data demonstrate that βarrestin2 can act as a ‘bonafide' signalling molecule even in the absence of activated receptor. PMID:15385966

Identification of structural protein-protein interactions of herpes simplex virus type 1.

Science.gov (United States)

Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

2008-09-01

In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

A domain-based approach to predict protein-protein interactions

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Resat Haluk

2007-06-01

Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

Interaction of Proteins Identified in Human Thyroid Cells

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Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

2013-01-01

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

Interaction of Proteins Identified in Human Thyroid Cells

Directory of Open Access Journals (Sweden)

Jessica Pietsch

2013-01-01

Full Text Available Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains.

Intercellular protein-protein interactions at synapses.

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Yang, Xiaofei; Hou, Dongmei; Jiang, Wei; Zhang, Chen

2014-06-01

Chemical synapses are asymmetric intercellular junctions through which neurons send nerve impulses to communicate with other neurons or excitable cells. The appropriate formation of synapses, both spatially and temporally, is essential for brain function and depends on the intercellular protein-protein interactions of cell adhesion molecules (CAMs) at synaptic clefts. The CAM proteins link pre- and post-synaptic sites, and play essential roles in promoting synapse formation and maturation, maintaining synapse number and type, accumulating neurotransmitter receptors and ion channels, controlling neuronal differentiation, and even regulating synaptic plasticity directly. Alteration of the interactions of CAMs leads to structural and functional impairments, which results in many neurological disorders, such as autism, Alzheimer's disease and schizophrenia. Therefore, it is crucial to understand the functions of CAMs during development and in the mature neural system, as well as in the pathogenesis of some neurological disorders. Here, we review the function of the major classes of CAMs, and how dysfunction of CAMs relates to several neurological disorders.

Phthalic Acid Chemical Probes Synthesized for Protein-Protein Interaction Analysis

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Chin-Jen Wu

2013-06-01

Full Text Available Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP. According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES was deposited on silicon dioxides (SiO2 particles and phthalate chemical probes were manufactured from phthalic acid and APTES–SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

Prediction of protein-protein interactions between viruses and human by an SVM model

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Cui Guangyu

2012-05-01

Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

Science.gov (United States)

Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Evidence of probabilistic behaviour in protein interaction networks

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Reifman Jaques

2008-01-01

Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

Science.gov (United States)

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

NatalieQ: A web server for protein-protein interaction network querying

NARCIS (Netherlands)

El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

2014-01-01

Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

Science.gov (United States)

Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

Science.gov (United States)

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells

Full Data of Yeast Interacting Proteins Database (Original Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Yeast Interacting Proteins Database Full Data of Yeast Interacting Proteins Database (Origin...al Version) Data detail Data name Full Data of Yeast Interacting Proteins Database (Original Version) DOI 10....18908/lsdba.nbdc00742-004 Description of data contents The entire data in the Yeast Interacting Proteins Database...eir interactions are required. Several sources including YPD (Yeast Proteome Database, Costanzo, M. C., Hoga...ematic name in the SGD (Saccharomyces Genome Database; http://www.yeastgenome.org /). Bait gene name The gen

From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

Directory of Open Access Journals (Sweden)

Mu Gao

2009-03-01

Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

Yeast Interacting Proteins Database: YGL127C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ith protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regula...rotein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

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Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

Porcine Reproductive and Respiratory Syndrome Virus Nucleocapsid Protein Interacts with Nsp9 and Cellular DHX9 To Regulate Viral RNA Synthesis.

Science.gov (United States)

Liu, Long; Tian, Jiao; Nan, Hao; Tian, Mengmeng; Li, Yuan; Xu, Xiaodong; Huang, Baicheng; Zhou, Enmin; Hiscox, Julian A; Chen, Hongying

2016-06-01

Porcine reproductive and respiratory syndrome virus (PRRSV) nucleocapsid (N) protein is the main component of the viral capsid to encapsulate viral RNA, and it is also a multifunctional protein involved in the regulation of host cell processes. Nonstructural protein 9 (Nsp9) is the RNA-dependent RNA polymerase that plays a critical role in viral RNA transcription and replication. In this study, we demonstrate that PRRSV N protein is bound to Nsp9 by protein-protein interaction and that the contacting surface on Nsp9 is located in the two predicted α-helixes formed by 48 residues at the C-terminal end of the protein. Mutagenesis analyses identified E646, E608, and E611 on Nsp9 and Q85 on the N protein as the pivotal residues participating in the N-Nsp9 interaction. By overexpressing the N protein binding fragment of Nsp9 in infected Marc-145 cells, the synthesis of viral RNAs, as well as the production of infectious progeny viruses, was dramatically inhibited, suggesting that Nsp9-N protein association is involved in the process of viral RNA production. In addition, we show that PRRSV N interacts with cellular RNA helicase DHX9 and redistributes the protein into the cytoplasm. Knockdown of DHX9 increased the ratio of short subgenomic mRNAs (sgmRNAs); in contrast, DHX9 overexpression benefited the synthesis of longer sgmRNAs and the viral genomic RNA (gRNA). These results imply that DHX9 is recruited by the N protein in PRRSV infection to regulate viral RNA synthesis. We postulate that N and DHX9 may act as antiattenuation factors for the continuous elongation of nascent transcript during negative-strand RNA synthesis. It is unclear whether the N protein of PRRSV is involved in regulation of the viral RNA production process. In this report, we demonstrate that the N protein of the arterivirus PRRSV participates in viral RNA replication and transcription through interacting with Nsp9 and its RdRp and recruiting cellular RNA helicase to promote the production of

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

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Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Yeast Interacting Proteins Database: YOR047C, YKL038W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available racts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a...Bait description Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose senso...rs Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator of the tra

Yeast Interacting Proteins Database: YFR049W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator... (0) YOR047C STD1 Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sens...ors Snf3p and Rgt2p, and TATA-binding protein Spt15p; ac

Yeast Interacting Proteins Database: YGL145W, YNL258C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ripheral membrane protein required for Golgi-to-ER retrograde traffic; component ... membrane protein required for Golgi-to-ER retrograde traffic; component of the ER target site that interact

A rice kinase-protein interaction map.

Science.gov (United States)

Ding, Xiaodong; Richter, Todd; Chen, Mei; Fujii, Hiroaki; Seo, Young Su; Xie, Mingtang; Zheng, Xianwu; Kanrar, Siddhartha; Stevenson, Rebecca A; Dardick, Christopher; Li, Ying; Jiang, Hao; Zhang, Yan; Yu, Fahong; Bartley, Laura E; Chern, Mawsheng; Bart, Rebecca; Chen, Xiuhua; Zhu, Lihuang; Farmerie, William G; Gribskov, Michael; Zhu, Jian-Kang; Fromm, Michael E; Ronald, Pamela C; Song, Wen-Yuan

2009-03-01

Plants uniquely contain large numbers of protein kinases, and for the vast majority of the 1,429 kinases predicted in the rice (Oryza sativa) genome, little is known of their functions. Genetic approaches often fail to produce observable phenotypes; thus, new strategies are needed to delineate kinase function. We previously developed a cost-effective high-throughput yeast two-hybrid system. Using this system, we have generated a protein interaction map of 116 representative rice kinases and 254 of their interacting proteins. Overall, the resulting interaction map supports a large number of known or predicted kinase-protein interactions from both plants and animals and reveals many new functional insights. Notably, we found a potential widespread role for E3 ubiquitin ligases in pathogen defense signaling mediated by receptor-like kinases, particularly by the kinases that may have evolved from recently expanded kinase subfamilies in rice. We anticipate that the data provided here will serve as a foundation for targeted functional studies in rice and other plants. The application of yeast two-hybrid and TAPtag analyses for large-scale plant protein interaction studies is also discussed.

MERTK interactions with SH2-domain proteins in the retinal pigment epithelium.

Science.gov (United States)

Shelby, Shameka J; Colwill, Karen; Dhe-Paganon, Sirano; Pawson, Tony; Thompson, Debra A

2013-01-01

The receptor tyrosine kinase MERTK plays an essential role in the phagocytic uptake of shed photoreceptor membranes by the retinal pigment epithelium (RPE). A fundamental aspect of signal transduction by receptor tyrosine kinases involves autophosphorylation of tyrosine residues that recruit Src-homology 2 (SH2)-domain proteins to the receptor intracellular domain. The goal of the current study was to evaluate the interactions of human MERTK with SH2-domain proteins present in the RPE. The MERTK intracellular domain was expressed as a 6xHis-fusion protein (6xHis-rMERTK(571-999)), purified and phosphorylated. Ni(2+)-NTA pull downs were performed using 6xHis-rMERTK(571-999) in incubations with recombinant phosphotyrosine-recognition sequences expressed as GST-fusion proteins. In addition, pull downs of native SH2-domain proteins were performed using 6xHis-rMERTK(571-999) and protein homogenates from rat RPE/choroid. For both recombinant and native proteins, western analysis detected MERTK interactions with GRB2, PIK3R1 (P85α), VAV3, and SRC. Immunohistochemical analysis localized each protein to mouse RPE. In cultured RPE-J cells incubated with rod outer segments (OS), siRNA knockdown of Grb2 had no effect on OS binding, but significantly reduced OS uptake. Pik3r1 localized to early phagosomes along with Rab5 and Eea1. Phosphorylation and activation of Src was detected downstream of phagocytosis and Mertk activation. These findings suggest that MERTK signaling in the RPE involves a cohort of SH2-domain proteins with the potential to regulate both cytoskeletal rearrangement and membrane movement. Identification of the SH2-domain signaling partners of MERTK is an important step toward further defining the mechanism of RPE phagocytosis that is central to the function and survival of the retina.

MERTK interactions with SH2-domain proteins in the retinal pigment epithelium.

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Shameka J Shelby

Full Text Available The receptor tyrosine kinase MERTK plays an essential role in the phagocytic uptake of shed photoreceptor membranes by the retinal pigment epithelium (RPE. A fundamental aspect of signal transduction by receptor tyrosine kinases involves autophosphorylation of tyrosine residues that recruit Src-homology 2 (SH2-domain proteins to the receptor intracellular domain. The goal of the current study was to evaluate the interactions of human MERTK with SH2-domain proteins present in the RPE. The MERTK intracellular domain was expressed as a 6xHis-fusion protein (6xHis-rMERTK(571-999, purified and phosphorylated. Ni(2+-NTA pull downs were performed using 6xHis-rMERTK(571-999 in incubations with recombinant phosphotyrosine-recognition sequences expressed as GST-fusion proteins. In addition, pull downs of native SH2-domain proteins were performed using 6xHis-rMERTK(571-999 and protein homogenates from rat RPE/choroid. For both recombinant and native proteins, western analysis detected MERTK interactions with GRB2, PIK3R1 (P85α, VAV3, and SRC. Immunohistochemical analysis localized each protein to mouse RPE. In cultured RPE-J cells incubated with rod outer segments (OS, siRNA knockdown of Grb2 had no effect on OS binding, but significantly reduced OS uptake. Pik3r1 localized to early phagosomes along with Rab5 and Eea1. Phosphorylation and activation of Src was detected downstream of phagocytosis and Mertk activation. These findings suggest that MERTK signaling in the RPE involves a cohort of SH2-domain proteins with the potential to regulate both cytoskeletal rearrangement and membrane movement. Identification of the SH2-domain signaling partners of MERTK is an important step toward further defining the mechanism of RPE phagocytosis that is central to the function and survival of the retina.

Filtering high-throughput protein-protein interaction data using a combination of genomic features

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Patil Ashwini

2005-04-01

Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

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Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

Analysis of Protein-Membrane Interactions

DEFF Research Database (Denmark)

Kemmer, Gerdi Christine

Cellular membranes are complex structures, consisting of hundreds of different lipids and proteins. These membranes act as barriers between distinct environments, constituting hot spots for many essential functions of the cell, including signaling, energy conversion, and transport. These functions....... Discovered interactions were then probed on the level of the membrane using liposome-based assays. In the second part, a transmembrane protein was investigated. Assays to probe activity of the plasma membrane ATPase (Arabidopsis thaliana H+ -ATPase isoform 2 (AHA2)) in single liposomes using both giant...... are implemented by soluble proteins reversibly binding to, as well as by integral membrane proteins embedded in, cellular membranes. The activity and interaction of these proteins is furthermore modulated by the lipids of the membrane. Here, liposomes were used as model membrane systems to investigate...

The Molecular Interaction of CAR and JAML Recruits the Central Cell Signal Transducer PI3K

Energy Technology Data Exchange (ETDEWEB)

Verdino, Petra; Witherden, Deborah A.; Havran, Wendy L.; Wilson, Ian A. (Scripps)

2010-11-15

Coxsackie and adenovirus receptor (CAR) is the primary cellular receptor for group B coxsackieviruses and most adenovirus serotypes and plays a crucial role in adenoviral gene therapy. Recent discovery of the interaction between junctional adhesion molecule-like protein (JAML) and CAR uncovered important functional roles in immunity, inflammation, and tissue homeostasis. Crystal structures of JAML ectodomain (2.2 angstroms) and its complex with CAR (2.8 angstroms) reveal an unusual immunoglobulin-domain assembly for JAML and a charged interface that confers high specificity. Biochemical and mutagenesis studies illustrate how CAR-mediated clustering of JAML recruits phosphoinositide 3-kinase (P13K) to a JAML intracellular sequence motif as delineated for the {alpha}{beta} T cell costimulatory receptor CD28. Thus, CAR and JAML are cell signaling receptors of the immune system with implications for asthma, cancer, and chronic nonhealing wounds.

Nuclear Protein Sam68 Interacts with the Enterovirus 71 Internal Ribosome Entry Site and Positively Regulates Viral Protein Translation.

Science.gov (United States)

Zhang, Hua; Song, Lei; Cong, Haolong; Tien, Po

2015-10-01

Enterovirus 71 (EV71) recruits various cellular factors to assist in the replication and translation of its genome. Identification of the host factors involved in the EV71 life cycle not only will enable a better understanding of the infection mechanism but also has the potential to be of use in the development of antiviral therapeutics. In this study, we demonstrated that the cellular factor 68-kDa Src-associated protein in mitosis (Sam68) acts as an internal ribosome entry site (IRES) trans-acting factor (ITAF) that binds specifically to the EV71 5' untranslated region (5'UTR). Interaction sites in both the viral IRES (stem-loops IV and V) and the heterogeneous nuclear ribonucleoprotein K homology (KH) domain of Sam68 protein were further mapped using an electrophoretic mobility shift assay (EMSA) and biotin RNA pulldown assay. More importantly, dual-luciferase (firefly) reporter analysis suggested that overexpression of Sam68 positively regulated IRES-dependent translation of virus proteins. In contrast, both IRES activity and viral protein translation significantly decreased in Sam68 knockdown cells compared with the negative-control cells treated with short hairpin RNA (shRNA). However, downregulation of Sam68 did not have a significant inhibitory effect on the accumulation of the EV71 genome. Moreover, Sam68 was redistributed from the nucleus to the cytoplasm and interacts with cellular factors, such as poly(rC)-binding protein 2 (PCBP2) and poly(A)-binding protein (PABP), during EV71 infection. The cytoplasmic relocalization of Sam68 in EV71-infected cells may be involved in the enhancement of EV71 IRES-mediated translation. Since Sam68 is known to be a RNA-binding protein, these results provide direct evidence that Sam68 is a novel ITAF that interacts with EV71 IRES and positively regulates viral protein translation. The nuclear protein Sam68 is found as an additional new host factor that interacts with the EV71 IRES during infection and could potentially

Functional interaction between Smad, CREB binding protein, and p68 RNA helicase

International Nuclear Information System (INIS)

Warner, Dennis R.; Bhattacherjee, Vasker; Yin, Xiaolong; Singh, Saurabh; Mukhopadhyay, Partha; Pisano, M. Michele; Greene, Robert M.

2004-01-01

The transforming growth factors β control a diversity of biological processes including cellular proliferation, differentiation, apoptosis, and extracellular matrix production, and are critical effectors of embryonic patterning and development, including that of the orofacial region. TGFβ superfamily members signal through specific cell surface receptors that phosphorylate the cytoplasmic Smad proteins, resulting in their translocation to the nucleus and interaction with promoters of TGFβ-responsive genes. Subsequent alterations in transcription are cell type-specific and dependent on recruitment to the Smad/transcription factor complex of coactivators, such as CBP and p300, or corepressors, such as c-ski and SnoN. Since the affinity of Smads for DNA is generally low, additional accessory proteins that facilitate Smad/DNA binding are required, and are often cell- and tissue-specific. In order to identify novel Smad 3 binding proteins in developing orofacial tissue, a yeast two hybrid assay was employed in which the MH2 domain of Smad 3 was used to screen an expression library derived from mouse embryonic orofacial tissue. The RNA helicase, p68, was identified as a unique Smad binding protein, and the specificity of the interaction was confirmed through various in vitro and in vivo assays. Co-expression of Smad 3 and a CBP-Gal4 DNA binding domain fusion protein in a Gal4-luciferase reporter assay resulted in increased TGFβ-stimulated reporter gene transcription. Moreover, co-expression of p68 RNA helicase along with Smad 3 and CBP-Gal4 resulted in synergistic activation of Gal4-luciferase reporter expression. Collectively, these data indicate that the RNA helicase, p68, can directly interact with Smad 3 resulting in formation of a transcriptionally active ternary complex containing Smad 3, p68, and CBP. This offers a means of enhancing TGFβ-mediated cellular responses in developing orofacial tissue

A selection that reports on protein-protein interactions within a thermophilic bacterium.

Science.gov (United States)

Nguyen, Peter Q; Silberg, Jonathan J

2010-07-01

Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions.

A method for investigating protein-protein interactions related to Salmonella typhimurium pathogenesis

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Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2009-02-10

We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .

Prediction and characterization of protein-protein interaction networks in swine

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Wang Fen

2012-01-01

Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

Yeast Interacting Proteins Database: YOR358W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act...rotein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator o

Predicting and validating protein interactions using network structure.

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Pao-Yang Chen

2008-07-01

Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

Protein-protein interaction network-based detection of functionally similar proteins within species.

Science.gov (United States)

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Transcription Factor Functional Protein-Protein Interactions in Plant Defense Responses

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Murilo S. Alves

2014-03-01

Full Text Available Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP, amino-acid sequence WRKYGQK (WRKY, myelocytomatosis related proteins (MYC, myeloblastosis related proteins (MYB, APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP and no apical meristem (NAM, Arabidopsis transcription activation factor (ATAF, and cup-shaped cotyledon (CUC (NAC. We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses.

The geometric framework for nutrition reveals interactions between protein and carbohydrate during larval growth in honey bees

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Bryan R. Helm

2017-06-01

Full Text Available In holometabolous insects, larval nutrition affects adult body size, a life history trait with a profound influence on performance and fitness. Individual nutritional components of larval diets are often complex and may interact with one another, necessitating the use of a geometric framework for elucidating nutritional effects. In the honey bee, Apis mellifera, nurse bees provision food to developing larvae, directly moderating growth rates and caste development. However, the eusocial nature of honey bees makes nutritional studies challenging, because diet components cannot be systematically manipulated in the hive. Using in vitro rearing, we investigated the roles and interactions between carbohydrate and protein content on larval survival, growth, and development in A. mellifera. We applied a geometric framework to determine how these two nutritional components interact across nine artificial diets. Honey bees successfully completed larval development under a wide range of protein and carbohydrate contents, with the medium protein (∼5% diet having the highest survival. Protein and carbohydrate both had significant and non-linear effects on growth rate, with the highest growth rates observed on a medium-protein, low-carbohydrate diet. Diet composition did not have a statistically significant effect on development time. These results confirm previous findings that protein and carbohydrate content affect the growth of A. mellifera larvae. However, this study identified an interaction between carbohydrate and protein content that indicates a low-protein, high-carb diet has a negative effect on larval growth and survival. These results imply that worker recruitment in the hive would decline under low protein conditions, even when nectar abundance or honey stores are sufficient.

A new protein-protein interaction sensor based on tripartite split-GFP association.

Science.gov (United States)

Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

2013-10-04

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

Data management of protein interaction networks

CERN Document Server

Cannataro, Mario

2012-01-01

Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

Human microcephaly protein RTTN interacts with STIL and is required to build full-length centrioles.

Science.gov (United States)

Chen, Hsin-Yi; Wu, Chien-Ting; Tang, Chieh-Ju C; Lin, Yi-Nan; Wang, Won-Jing; Tang, Tang K

2017-08-15

Mutations in many centriolar protein-encoding genes cause primary microcephaly. Using super-resolution and electron microscopy, we find that the human microcephaly protein, RTTN, is recruited to the proximal end of the procentriole at early S phase, and is located at the inner luminal walls of centrioles. Further studies demonstrate that RTTN directly interacts with STIL and acts downstream of STIL-mediated centriole assembly. CRISPR/Cas9-mediated RTTN gene knockout in p53-deficient cells induce amplification of primitive procentriole bodies that lack the distal-half centriolar proteins, POC5 and POC1B. Additional analyses show that RTTN serves as an upstream effector of CEP295, which mediates the loading of POC1B and POC5 to the distal-half centrioles. Interestingly, the naturally occurring microcephaly-associated mutant, RTTN (A578P), shows a low affinity for STIL binding and blocks centriole assembly. These findings reveal that RTTN contributes to building full-length centrioles and illuminate the molecular mechanism through which the RTTN (A578P) mutation causes primary microcephaly.Mutations in many centriolar protein-encoding genes cause primary microcephaly. Here the authors show that human microcephaly protein RTTN directly interacts with STIL and acts downstream of STIL-mediated centriole assembly, contributing to building full-length centrioles.

Supplementary Material for: Potential impact of climate-related changes is buffered by differential responses to recruitment and interactions

KAUST Repository

Menge, Bruce A.; Hacker, Sally D.; Freidenburg, Tess; Lubchenco, Jane; Craig, Ryan; Rilov, Gil; Noble, Mae Marjore; Richmond, Erin

2016-01-01

Detection of ecosystem responsiveness to climatic perturbations can provide insight into climate change consequences. Recent analyses linking phytoplankton abundance and mussel recruitment to the North Pacific Gyre Oscillation (NPGO) revealed a paradox. Despite large increases in mussel recruitment beginning in 2000, adult mussel responses were idiosyncratic by site and intertidal zone, with no response at one long-term site, and increases in the low zone (1.5% per year) and decreases in the mid zone (1.3% per year) at the other. What are the mechanisms underlying these differential changes? Species interactions such as facilitation by barnacles and predation are potential determinants of successful mussel colonization. To evaluate these effects, we analyzed patterns of barnacle recruitment, determined if predation rate covaried with the increase in mussel recruitment, and tested facilitation interactions in a field experiment. Neither magnitude nor season of barnacle recruitment changed meaningfully with site or zone from the 1990s to the 2000s. In contrast to the relationship between NPGO and local-scale mussel recruitment, relationships between local-scale patterns of barnacle recruitment and climate indices were weak. Despite differences in rates of prey recruitment and abundance of sea stars in 1990–1991, 1999–2000, and 2007–2008, predation rates were nearly identical in experiments before, during, and after 1999–2000. The facilitation experiment showed that mussels M. trossulus only became abundant when barnacle recruitment was allowed, when abundance of barnacles reached high abundance of ∼50% cover, and when mussel recruitment was sufficiently high. Thus, in the low zone minimal changes in mussel abundance despite sharply increased recruitment rates are consistent with the hypothesis that change in adult mussel cover was buffered by the relative insensitivity of barnacle recruitment to climatic fluctuations, and a resultant lack of

Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

Science.gov (United States)

Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

2013-04-01

Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

Science.gov (United States)

Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

2011-06-01

Physics approaches focus on uncovering, modeling and quantitating the general principles governing the micro and macro universe. This has always been an important component of biological research, however recent advances in experimental techniques and the accumulation of unprecedented genome-scale experimental data produced by these novel technologies now allow for addressing fundamental questions on a large scale. These relate to molecular interactions, principles of bimolecular recognition, and mechanisms of signal propagation. The functioning of a cell requires a variety of intermolecular interactions including protein-protein, protein-DNA, protein-RNA, hormones, peptides, small molecules, lipids and more. Biomolecules work together to provide specific functions and perturbations in intermolecular communication channels often lead to cellular malfunction and disease. A full understanding of the interactome requires an in-depth grasp of the biophysical principles underlying individual interactions as well as their organization in cellular networks. Phenomena can be described at different levels of abstraction. Computational and systems biology strive to model cellular processes by integrating and analyzing complex data from multiple experimental sources using interdisciplinary tools. As a result, both the causal relationships between the variables and the general features of the system can be discovered, which even without knowing the details of the underlying mechanisms allow for putting forth hypotheses and predicting the behavior of the systems in response to perturbation. And here lies the strength of in silico models which provide control and predictive power. At the same time, the complexity of individual elements and molecules can be addressed by the fields of molecular biophysics, physical biology and structural biology, which focus on the underlying physico-chemical principles and may explain the molecular mechanisms of cellular function. In this issue

The role of exon shuffling in shaping protein-protein interaction networks

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França Gustavo S

2010-12-01

Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

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Vandepoele Klaas

2009-06-01

Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

Protein-material interactions: From micro-to-nano scale

International Nuclear Information System (INIS)

Tsapikouni, Theodora S.; Missirlis, Yannis F.

2008-01-01

The article presents a survey on the significance of protein-material interactions, the mechanisms which control them and the techniques used for their study. Protein-surface interactions play a key role in regenerative medicine, drug delivery, biosensor technology and chromatography, while it is related to various undesired effects such as biofouling and bio-prosthetic malfunction. Although the effects of protein-surface interaction concern the micro-scale, being sometimes obvious even with bare eyes, they derive from biophysical events at the nano-scale. The sequential steps for protein adsorption involve events at the single biomolecule level and the forces driving or inhibiting protein adsorption act at the molecular level too. Following the scaling of protein-surface interactions, various techniques have been developed for their study both in the micro- and nano-scale. Protein labelling with radioisotopes or fluorescent probes, colorimetric assays and the quartz crystal microbalance were the first techniques used to monitor protein adsorption isotherms, while the surface force apparatus was used to measure the interaction forces between protein layers at the micro-scale. Recently, more elaborate techniques like total internal reflection fluorescence (TIRF), Fourier transform infrared spectroscopy (FTIR), surface plasmon resonance, Raman spectroscopy, ellipsometry and time of flight secondary ion mass spectrometry (ToF-SIMS) have been applied for the investigation of protein density, structure or orientation at the interfaces. However, a turning point in the study of protein interactions with the surfaces was the invention and the wide-spread use of atomic force microscopy (AFM) which can both image single protein molecules on surfaces and directly measure the interaction force

RAIN: RNA-protein Association and Interaction Networks

DEFF Research Database (Denmark)

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

2017-01-01

is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data...

On the role of electrostatics on protein-protein interactions

Science.gov (United States)

Zhang, Zhe; Witham, Shawn; Alexov, Emil

2011-01-01

The role of electrostatics on protein-protein interactions and binding is reviewed in this article. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and basic electrostatic effects occurring upon the formation of the complex are discussed. The role of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated and indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartment. At the end, the similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity. PMID:21572182

GINS complex protein Sld5 recruits SIK1 to activate MCM helicase during DNA replication.

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Joshi, Kiranmai; Shah, Varun Jayeshkumar; Maddika, Subbareddy

2016-12-01

In eukaryotes, proper loading and activation of MCM helicase at chromosomal origins plays a central role in DNA replication. Activation of MCM helicase requires its association with CDC45-GINS complex, but the mechanism of how this complex activates MCM helicase is poorly understood. Here we identified SIK1 (salt-inducible kinase 1), an AMPK related protein kinase, as a molecular link that connects GINS complex with MCM helicase activity. We demonstrated that Sld5 a component of GINS complex interacts with SIK1 and recruits it to the sites of DNA replication at the onset of S phase. Depletion of SIK1 leads to defective DNA replication. Further, we showed that SIK1 phosphorylates MCM2 at five conserved residues at its N-terminus, which is essential for the activation of MCM helicase. Collectively, our results suggest SIK1 as a novel integral component of CMG replicative helicase during eukaryotic DNA replication. Copyright © 2016 Elsevier Inc. All rights reserved.

A mechanism for vertebrate Hedgehog signaling: recruitment to cilia and dissociation of SuFu–Gli protein complexes

OpenAIRE

Tukachinsky, Hanna; Lopez, Lyle V.; Salic, Adrian

2010-01-01

In vertebrates, Hedgehog (Hh) signaling initiated in primary cilia activates the membrane protein Smoothened (Smo) and leads to activation of Gli proteins, the transcriptional effectors of the pathway. In the absence of signaling, Gli proteins are inhibited by the cytoplasmic protein Suppressor of Fused (SuFu). It is unclear how Hh activates Gli and whether it directly regulates SuFu. We find that Hh stimulation quickly recruits endogenous SuFu–Gli complexes to cilia, suggesting a model in wh...

The simulation approach to lipid-protein interactions.

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Paramo, Teresa; Garzón, Diana; Holdbrook, Daniel A; Khalid, Syma; Bond, Peter J

2013-01-01

The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.

False positive reduction in protein-protein interaction predictions using gene ontology annotations

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Lin Yen-Han

2007-07-01

Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

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Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recruitment kinetics of DNA repair proteins Mdc1 and Rad52 but not 53BP1 depend on damage complexity.

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Volker Hable

Full Text Available The recruitment kinetics of double-strand break (DSB signaling and repair proteins Mdc1, 53BP1 and Rad52 into radiation-induced foci was studied by live-cell fluorescence microscopy after ion microirradiation. To investigate the influence of damage density and complexity on recruitment kinetics, which cannot be done by UV laser irradiation used in former studies, we utilized 43 MeV carbon ions with high linear energy transfer per ion (LET = 370 keV/µm to create a large fraction of clustered DSBs, thus forming complex DNA damage, and 20 MeV protons with low LET (LET = 2.6 keV/µm to create mainly isolated DSBs. Kinetics for all three proteins was characterized by a time lag period T(0 after irradiation, during which no foci are formed. Subsequently, the proteins accumulate into foci with characteristic mean recruitment times τ(1. Mdc1 accumulates faster (T(0 = 17 ± 2 s, τ(1 = 98 ± 11 s than 53BP1 (T(0 = 77 ± 7 s, τ(1 = 310 ± 60 s after high LET irradiation. However, recruitment of Mdc1 slows down (T(0 = 73 ± 16 s, τ(1 = 1050 ± 270 s after low LET irradiation. The recruitment kinetics of Rad52 is slower than that of Mdc1, but exhibits the same dependence on LET. In contrast, the mean recruitment time τ(1 of 53BP1 remains almost constant when varying LET. Comparison to literature data on Mdc1 recruitment after UV laser irradiation shows that this rather resembles recruitment after high than low LET ionizing radiation. So this work shows that damage quality has a large influence on repair processes and has to be considered when comparing different studies.

Parallel force assay for protein-protein interactions.

Science.gov (United States)

Aschenbrenner, Daniela; Pippig, Diana A; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E

2014-01-01

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.

Prediction of thermodynamic instabilities of protein solutions from simple protein–protein interactions

International Nuclear Information System (INIS)

D’Agostino, Tommaso; Solana, José Ramón; Emanuele, Antonio

2013-01-01

Highlights: ► We propose a model of effective protein–protein interaction embedding solvent effects. ► A previous square-well model is enhanced by giving to the interaction a free energy character. ► The temperature dependence of the interaction is due to entropic effects of the solvent. ► The validity of the original SW model is extended to entropy driven phase transitions. ► We get good fits for lysozyme and haemoglobin spinodal data taken from literature. - Abstract: Statistical thermodynamics of protein solutions is often studied in terms of simple, microscopic models of particles interacting via pairwise potentials. Such modelling can reproduce the short range structure of protein solutions at equilibrium and predict thermodynamics instabilities of these systems. We introduce a square well model of effective protein–protein interaction that embeds the solvent’s action. We modify an existing model [45] by considering a well depth having an explicit dependence on temperature, i.e. an explicit free energy character, thus encompassing the statistically relevant configurations of solvent molecules around proteins. We choose protein solutions exhibiting demixing upon temperature decrease (lysozyme, enthalpy driven) and upon temperature increase (haemoglobin, entropy driven). We obtain satisfactory fits of spinodal curves for both the two proteins without adding any mean field term, thus extending the validity of the original model. Our results underline the solvent role in modulating or stretching the interaction potential

Interaction between plate make and protein in protein crystallisation screening.

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Gordon J King

Full Text Available BACKGROUND: Protein crystallisation screening involves the parallel testing of large numbers of candidate conditions with the aim of identifying conditions suitable as a starting point for the production of diffraction quality crystals. Generally, condition screening is performed in 96-well plates. While previous studies have examined the effects of protein construct, protein purity, or crystallisation condition ingredients on protein crystallisation, few have examined the effect of the crystallisation plate. METHODOLOGY/PRINCIPAL FINDINGS: We performed a statistically rigorous examination of protein crystallisation, and evaluated interactions between crystallisation success and plate row/column, different plates of same make, different plate makes and different proteins. From our analysis of protein crystallisation, we found a significant interaction between plate make and the specific protein being crystallised. CONCLUSIONS/SIGNIFICANCE: Protein crystal structure determination is the principal method for determining protein structure but is limited by the need to produce crystals of the protein under study. Many important proteins are difficult to crystallize, so that identification of factors that assist crystallisation could open up the structure determination of these more challenging targets. Our findings suggest that protein crystallisation success may be improved by matching a protein with its optimal plate make.

Integral UBL domain proteins: a family of proteasome interacting proteins

DEFF Research Database (Denmark)

Hartmann-Petersen, Rasmus; Gordon, Colin

2004-01-01

The family of ubiquitin-like (UBL) domain proteins (UDPs) comprises a conserved group of proteins involved in a multitude of different cellular activities. However, recent studies on UBL-domain proteins indicate that these proteins appear to share a common property in their ability to interact...

Yeast Interacting Proteins Database: YOR302W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available rol of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt...tein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt1

Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

NARCIS (Netherlands)

Rahmani, Hossein

2012-01-01

This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

Crystal Structure of Bicc1 SAM Polymer and Mapping of Interactions between the Ciliopathy-Associated Proteins Bicc1, ANKS3, and ANKS6.

Science.gov (United States)

Rothé, Benjamin; Leettola, Catherine N; Leal-Esteban, Lucia; Cascio, Duilio; Fortier, Simon; Isenschmid, Manuela; Bowie, James U; Constam, Daniel B

2018-02-06

Head-to-tail polymers of sterile alpha motifs (SAM) can scaffold large macromolecular complexes. Several SAM-domain proteins that bind each other are mutated in patients with cystic kidneys or laterality defects, including the Ankyrin (ANK) and SAM domain-containing proteins ANKS6 and ANKS3, and the RNA-binding protein Bicc1. To address how their interactions are regulated, we first determined a high-resolution crystal structure of a Bicc1-SAM polymer, revealing a canonical SAM polymer with a high degree of flexibility in the subunit interface orientations. We further mapped interactions between full-length and distinct domains of Bicc1, ANKS3, and ANKS6. Neither ANKS3 nor ANKS6 alone formed macroscopic homopolymers in vivo. However, ANKS3 recruited ANKS6 to Bicc1, and the three proteins together cooperatively generated giant macromolecular complexes. Thus, the giant assemblies are shaped by SAM domains, their flanking sequences, and SAM-independent protein-protein and protein-mRNA interactions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Protein-protein interactions within late pre-40S ribosomes.

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Melody G Campbell

2011-01-01

Full Text Available Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.

E-recruitment

DEFF Research Database (Denmark)

Holm, Anna

2012-01-01

E-recruitment, also known as online or web-based recruitment, is little discussed in research from an organizational perspective. The purpose of this chapter is therefore to analyze and discuss the process of e-recruitment, its key constituents and organizing principles. In doing so I draw...... on the results of a qualitative study conducted in 2008-2009, and on data stemming from industrial reports, articles from practitioner magazines, and in-depth interviews. The chapter provides a summary of e-recruitment properties and a composite matrix of the overall elements of e-recruitment organizing. E-recruitment...... is viewed as a case of virtual organizing- the organization of processes and activities which, via technology and human agents, facilitate time- and space-independent interaction and collaboration. In closure I offer a brief discussion of implications of the findings for HR managers and professionals...

Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

Science.gov (United States)

DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Kinome signaling through regulated protein-protein interactions in normal and cancer cells.

Science.gov (United States)

Pawson, Tony; Kofler, Michael

2009-04-01

The flow of molecular information through normal and oncogenic signaling pathways frequently depends on protein phosphorylation, mediated by specific kinases, and the selective binding of the resulting phosphorylation sites to interaction domains present on downstream targets. This physical and functional interplay of catalytic and interaction domains can be clearly seen in cytoplasmic tyrosine kinases such as Src, Abl, Fes, and ZAP-70. Although the kinase and SH2 domains of these proteins possess similar intrinsic properties of phosphorylating tyrosine residues or binding phosphotyrosine sites, they also undergo intramolecular interactions when linked together, in a fashion that varies from protein to protein. These cooperative interactions can have diverse effects on substrate recognition and kinase activity, and provide a variety of mechanisms to link the stimulation of catalytic activity to substrate recognition. Taken together, these data have suggested how protein kinases, and the signaling pathways in which they are embedded, can evolve complex properties through the stepwise linkage of domains within single polypeptides or multi-protein assemblies.

GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

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Zheng Huiru

2009-01-01

Full Text Available Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases and non-interacting proteins (negative cases are essential to support computational prediction and validation of protein-protein interactions. Information on known interacting and non interacting proteins are usually stored within databases. Extraction of these data can be both complex and time consuming. Although, the automatic construction of reference datasets for classification is a useful resource for researchers no public resource currently exists to perform this task. Results GRIP (Gold Reference dataset constructor from Information on Protein complexes is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae. Conclusion GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/.

The effect of protein-protein and protein-membrane interactions on membrane fouling in ultrafiltration

NARCIS (Netherlands)

Huisman, I.H.; Prádanos, P.; Hernández, A.

2000-01-01

It was studied how protein-protein and protein-membrane interactions influence the filtration performance during the ultrafiltration of protein solutions over polymeric membranes. This was done by measuring flux, streaming potential, and protein transmission during filtration of bovine serum albumin

Core Data of Yeast Interacting Proteins Database (Original Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available y are in the reverse direction. *1 A comprehensive two-hybrid analysis to explore the yeast protein interact...s. 2000 Jan 1;28(1):73-6. *2 The yeast proteome database (YPD) and Caenorhabditis elegans proteome database (WormPD): comprehensive...000 Jan 1;28(1):73-6. *3 A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisia

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

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Barkallah Insaf

2009-04-01

Full Text Available Abstract Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R1 (Deira, resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP and the Protein Structural Interactome (PSI-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

Uncovering Viral Protein-Protein Interactions and their Role in Arenavirus Life Cycle

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Nora López

2012-09-01

Full Text Available The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article.

Herp enhances ER-associated protein degradation by recruiting ubiquilins

International Nuclear Information System (INIS)

Kim, Tae-Yeon; Kim, Eunmin; Yoon, Sungjoo Kim; Yoon, Jong-Bok

2008-01-01

ER-associated protein degradation (ERAD) is a protein quality control system of ER, which eliminates misfolded proteins by proteasome-dependent degradation and ensures export of only properly folded proteins from ER. Herp, an ER membrane protein upregulated by ER stress, is implicated in regulation of ERAD. In the present study, we show that Herp interacts with members of the ubiquilin family, which function as a shuttle factor to deliver ubiquitinated substrates to the proteasome for degradation. Knockdown of ubiquilin expression by small interfering RNA stabilized the ERAD substrate CD3δ, whereas it did not alter or increased degradation of non-ERAD substrates tested. CD3δ was stabilized by overexpressed Herp mutants which were capable of binding to ubiquilins but were impaired in ER membrane targeting by deletion of the transmembrane domain. Our data suggest that Herp binding to ubiquilin proteins plays an important role in the ERAD pathway and that ubiquilins are specifically involved in degradation of only a subset of ubiquitinated targets, including Herp-dependent ERAD substrates

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

DEFF Research Database (Denmark)

Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

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Peiying Ruan

Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.

Arabidopsis GCP3-interacting protein 1/MOZART 1 is an integral component of the γ-tubulin-containing microtubule nucleating complex.

Science.gov (United States)

Nakamura, Masayoshi; Yagi, Noriyoshi; Kato, Takehide; Fujita, Satoshi; Kawashima, Noriyuki; Ehrhardt, David W; Hashimoto, Takashi

2012-07-01

Microtubules in eukaryotic cells are nucleated from ring-shaped complexes that contain γ-tubulin and a family of homologous γ-tubulin complex proteins (GCPs), but the subunit composition of the complexes can vary among fungi, animals and plants. Arabidopsis GCP3-interacting protein 1 (GIP1), a small protein with no homology to the GCP family, interacts with GCP3 in vitro, and is a plant homolog of vertebrate mitotic-spindle organizing protein associated with a ring of γ-tubulin 1 (MOZART1), a recently identified component of the γ-tubulin complex in human cell lines. In this study, we characterized two closely related Arabidopsis GIP1s: GIP1a and GIP1b. Single mutants of gip1a and gip1b were indistinguishable from wild-type plants, but their double mutant was embryonic lethal, and showed impaired development of male gametophytes. Functional fusions of GIP1a with green fluorescent protein (GFP) were used to purify GIP1a-containing complexes from Arabidopsis plants, which contained all the subunits (except NEDD1) previously identified in the Arabidopsis γ-tubulin complexes. GIP1a and GIP1b interacted specifically with Arabidopsis GCP3 in yeast. GFP-GIP1a labeled mitotic microtubule arrays in a pattern largely consistent with, but partly distinct from, the localization of the γ-tubulin complex containing GCP2 or GCP3 in planta. In interphase cortical arrays, the labeled complexes were preferentially recruited to existing microtubules, from which new microtubules were efficiently nucleated. However, in contrast to complexes labeled with tagged GCP2 or GCP3, their recruitment to cortical areas with no microtubules was rarely observed. These results indicate that GIP1/MOZART1 is an integral component of a subset of the Arabidopsis γ-tubulin complexes. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.

Centrobin-Centrosomal Protein 4.1-associated Protein (CPAP) Interaction Promotes CPAP Localization to the Centrioles during Centriole Duplication*

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Gudi, Radhika; Zou, Chaozhong; Dhar, Jayeeta; Gao, Qingshen; Vasu, Chenthamarakshan

2014-01-01

Centriole duplication is the process by which two new daughter centrioles are generated from the proximal end of preexisting mother centrioles. Accurate centriole duplication is important for many cellular and physiological events, including cell division and ciliogenesis. Centrosomal protein 4.1-associated protein (CPAP), centrosomal protein of 152 kDa (CEP152), and centrobin are known to be essential for centriole duplication. However, the precise mechanism by which they contribute to centriole duplication is not known. In this study, we show that centrobin interacts with CEP152 and CPAP, and the centrobin-CPAP interaction is critical for centriole duplication. Although depletion of centrobin from cells did not have an effect on the centriolar levels of CEP152, it caused the disappearance of CPAP from both the preexisting and newly formed centrioles. Moreover, exogenous expression of the CPAP-binding fragment of centrobin also caused the disappearance of CPAP from both the preexisting and newly synthesized centrioles, possibly in a dominant negative manner, thereby inhibiting centriole duplication and the PLK4 overexpression-mediated centrosome amplification. Interestingly, exogenous overexpression of CPAP in the centrobin-depleted cells did not restore CPAP localization to the centrioles. However, restoration of centrobin expression in the centrobin-depleted cells led to the reappearance of centriolar CPAP. Hence, we conclude that centrobin-CPAP interaction is critical for the recruitment of CPAP to procentrioles to promote the elongation of daughter centrioles and for the persistence of CPAP on preexisting mother centrioles. Our study indicates that regulation of CPAP levels on the centrioles by centrobin is critical for preserving the normal size, shape, and number of centrioles in the cell. PMID:24700465

Relative quantification of protein-protein interactions using a dual luciferase reporter pull-down assay system.

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Shuaizheng Jia

Full Text Available The identification and quantitative analysis of protein-protein interactions are essential to the functional characterization of proteins in the post-proteomics era. The methods currently available are generally time-consuming, technically complicated, insensitive and/or semi-quantitative. The lack of simple, sensitive approaches to precisely quantify protein-protein interactions still prevents our understanding of the functions of many proteins. Here, we develop a novel dual luciferase reporter pull-down assay by combining a biotinylated Firefly luciferase pull-down assay with a dual luciferase reporter assay. The biotinylated Firefly luciferase-tagged protein enables rapid and efficient isolation of a putative Renilla luciferase-tagged binding protein from a relatively small amount of sample. Both of these proteins can be quantitatively detected using the dual luciferase reporter assay system. Protein-protein interactions, including Fos-Jun located in the nucleus; MAVS-TRAF3 in cytoplasm; inducible IRF3 dimerization; viral protein-regulated interactions, such as MAVS-MAVS and MAVS-TRAF3; IRF3 dimerization; and protein interaction domain mapping, are studied using this novel assay system. Herein, we demonstrate that this dual luciferase reporter pull-down assay enables the quantification of the relative amounts of interacting proteins that bind to streptavidin-coupled beads for protein purification. This study provides a simple, rapid, sensitive, and efficient approach to identify and quantify relative protein-protein interactions. Importantly, the dual luciferase reporter pull-down method will facilitate the functional determination of proteins.

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

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Sony Malhotra

Full Text Available Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

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Jillian L Blatti

Full Text Available Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP and thioesterase (TE govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

Protein-Protein Interaction Reagents | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

A protein domain interaction interface database: InterPare

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Lee Jungsul

2005-08-01

Full Text Available Abstract Background Most proteins function by interacting with other molecules. Their interaction interfaces are highly conserved throughout evolution to avoid undesirable interactions that lead to fatal disorders in cells. Rational drug discovery includes computational methods to identify the interaction sites of lead compounds to the target molecules. Identifying and classifying protein interaction interfaces on a large scale can help researchers discover drug targets more efficiently. Description We introduce a large-scale protein domain interaction interface database called InterPare http://interpare.net. It contains both inter-chain (between chains interfaces and intra-chain (within chain interfaces. InterPare uses three methods to detect interfaces: 1 the geometric distance method for checking the distance between atoms that belong to different domains, 2 Accessible Surface Area (ASA, a method for detecting the buried region of a protein that is detached from a solvent when forming multimers or complexes, and 3 the Voronoi diagram, a computational geometry method that uses a mathematical definition of interface regions. InterPare includes visualization tools to display protein interior, surface, and interaction interfaces. It also provides statistics such as the amino acid propensities of queried protein according to its interior, surface, and interface region. The atom coordinates that belong to interface, surface, and interior regions can be downloaded from the website. Conclusion InterPare is an open and public database server for protein interaction interface information. It contains the large-scale interface data for proteins whose 3D-structures are known. As of November 2004, there were 10,583 (Geometric distance, 10,431 (ASA, and 11,010 (Voronoi diagram entries in the Protein Data Bank (PDB containing interfaces, according to the above three methods. In the case of the geometric distance method, there are 31,620 inter-chain domain

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

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Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

(S)Pinning down protein interactions by NMR

DEFF Research Database (Denmark)

Teilum, Kaare; Kunze, Micha Ben Achim; Erlendsson, Simon

2017-01-01

Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions...... all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative...... descriptions of protein interactions. In this review we provide an easy-access approach to NMR for the non-NMR specialist and describe how and when solution state NMR spectroscopy is the method of choice for addressing protein ligand interaction. We describe very briefly the theoretical background...

Specificity and evolvability in eukaryotic protein interaction networks.

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Pedro Beltrao

2007-02-01

Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

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Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

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Eric A Yen

2014-05-01

Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

Myeloproliferative disorder FOP-FGFR1 fusion kinase recruits phosphoinositide-3 kinase and phospholipase Cγ at the centrosome

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Tassin Anne-Marie

2008-04-01

Full Text Available Abstract Background The t(6;8 translocation found in rare and agressive myeloproliferative disorders results in a chimeric gene encoding the FOP-FGFR1 fusion protein. This protein comprises the N-terminal region of the centrosomal protein FOP and the tyrosine kinase of the FGFR1 receptor. FOP-FGFR1 is localized at the centrosome where it exerts a constitutive kinase activity. Results We show that FOP-FGFR1 interacts with the large centrosomal protein CAP350 and that CAP350 is necessary for FOP-FGFR1 localisation at centrosome. FOP-FGFR1 activates the phosphoinositide-3 kinase (PI3K pathway. We show that p85 interacts with tyrosine 475 of FOP-FGFR1, which is located in a YXXM consensus binding sequence for an SH2 domain of p85. This interaction is in part responsible for PI3K activation. Ba/F3 cells that express FOP-FGFR1 mutated at tyrosine 475 have reduced proliferative ability. Treatment with PI3K pathway inhibitors induces death of FOP-FGFR1 expressing cells. FOP-FGFR1 also recruits phospholipase Cγ1 (PLCγ1 at the centrosome. We show that this enzyme is recruited by FOP-FGFR1 at the centrosome during interphase. Conclusion These results delineate a particular type of oncogenic mechanism by which an ectopic kinase recruits its substrates at the centrosome whence unappropriate signaling induces continuous cell growth and MPD.

Energetics of the protein-DNA-water interaction

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Marabotti Anna

2007-01-01

Full Text Available Abstract Background To understand the energetics of the interaction between protein and DNA we analyzed 39 crystallographically characterized complexes with the HINT (Hydropathic INTeractions computational model. HINT is an empirical free energy force field based on solvent partitioning of small molecules between water and 1-octanol. Our previous studies on protein-ligand complexes demonstrated that free energy predictions were significantly improved by taking into account the energetic contribution of water molecules that form at least one hydrogen bond with each interacting species. Results An initial correlation between the calculated HINT scores and the experimentally determined binding free energies in the protein-DNA system exhibited a relatively poor r2 of 0.21 and standard error of ± 1.71 kcal mol-1. However, the inclusion of 261 waters that bridge protein and DNA improved the HINT score-free energy correlation to an r2 of 0.56 and standard error of ± 1.28 kcal mol-1. Analysis of the water role and energy contributions indicate that 46% of the bridging waters act as linkers between amino acids and nucleotide bases at the protein-DNA interface, while the remaining 54% are largely involved in screening unfavorable electrostatic contacts. Conclusion This study quantifies the key energetic role of bridging waters in protein-DNA associations. In addition, the relevant role of hydrophobic interactions and entropy in driving protein-DNA association is indicated by analyses of interaction character showing that, together, the favorable polar and unfavorable polar/hydrophobic-polar interactions (i.e., desolvation mostly cancel.

In vivo interactions between the proteins of infectious bursal disease virus: capsid protein VP3 interacts with the RNA dependent polymerase VP1

NARCIS (Netherlands)

Tacken, M.G.J.; Rottier, P.J.M.; Gielkens, A.L.J.; Peeters, B.P.H.

2000-01-01

Little is known about the intermolecular interactions between the viral proteins of infectious bursal disease virus (IBDV). By using the yeast two-hybrid system, which allows the detection of protein-protein interactions in vivo, all possible interactions were tested by fusing the viral proteins to

Interactions in vivo between the proteins of infectious bursal disease virus: capsid protein VP3 interacts with the RNA-dependent polymerase, VP1

NARCIS (Netherlands)

Tacken, M.G.J.; Rottier, P.J.M.; Gielkens, A.L.J.; Peeters, B.P.H.

2000-01-01

Little is known about the intermolecular interactions between the viral proteins of infectious bursal disease virus (IBDV). By using the yeast two-hybrid system, which allows the detection of protein-protein interactions in vivo, all possible interactions were tested by fusing the viral proteins to

Cell penetrating peptides to dissect host-pathogen protein-protein interactions in Theileria -transformed leukocytes

KAUST Repository

Haidar, Malak; de Laté , Perle Latré ; Kennedy, Eileen J.; Langsley, Gordon

2017-01-01

One powerful application of cell penetrating peptides is the delivery into cells of molecules that function as specific competitors or inhibitors of protein-protein interactions. Ablating defined protein-protein interactions is a refined way

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

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Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

Targeting protein-protein interaction between MLL1 and reciprocal proteins for leukemia therapy.

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Wang, Zhi-Hui; Li, Dong-Dong; Chen, Wei-Lin; You, Qi-Dong; Guo, Xiao-Ke

2018-01-15

The mixed lineage leukemia protein-1 (MLL1), as a lysine methyltransferase, predominantly regulates the methylation of histone H3 lysine 4 (H3K4) and functions in hematopoietic stem cell (HSC) self-renewal. MLL1 gene fuses with partner genes that results in the generation of MLL1 fusion proteins (MLL1-FPs), which are frequently detected in acute leukemia. In the progress of leukemogenesis, a great deal of proteins cooperate with MLL1 to form multiprotein complexes serving for the dysregulation of H3K4 methylation, the overexpression of homeobox (HOX) cluster genes, and the consequent generation of leukemia. Hence, disrupting the interactions between MLL1 and the reciprocal proteins has been considered to be a new treatment strategy for leukemia. Here, we reviewed potential protein-protein interactions (PPIs) between MLL1 and its reciprocal proteins, and summarized the inhibitors to target MLL1 PPIs. The druggability of MLL1 PPIs for leukemia were also discussed. Copyright © 2017. Published by Elsevier Ltd.

Drosophila Protein interaction Map (DPiM)

OpenAIRE

Guruharsha, K.G.; Obar, Robert A.; Mintseris, Julian; Aishwarya, K.; Krishnan, R.T.; VijayRaghavan, K.; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when,...

A Library of Plasmodium vivax Recombinant Merozoite Proteins Reveals New Vaccine Candidates and Protein-Protein Interactions

Science.gov (United States)

Hostetler, Jessica B.; Sharma, Sumana; Bartholdson, S. Josefin; Wright, Gavin J.; Fairhurst, Rick M.; Rayner, Julian C.

2015-01-01

Background A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP) and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC), and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion. Methodology/Principal Findings We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further

Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

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Carson M Andorf

Full Text Available Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners.Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques.Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions.We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

Science.gov (United States)

Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

2017-12-01

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

Science.gov (United States)

Hu, Xiaotang; Li, Hongbin

2014-10-01

Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Parallel force assay for protein-protein interactions.

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Daniela Aschenbrenner

Full Text Available Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

Directory of Open Access Journals (Sweden)

Ji'an Pan

Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

Protein-Protein Interactions of Viroporins in Coronaviruses and Paramyxoviruses: New Targets for Antivirals?

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Jaume Torres

2015-06-01

Full Text Available Viroporins are members of a rapidly growing family of channel-forming small polypeptides found in viruses. The present review will be focused on recent structural and protein-protein interaction information involving two viroporins found in enveloped viruses that target the respiratory tract; (i the envelope protein in coronaviruses and (ii the small hydrophobic protein in paramyxoviruses. Deletion of these two viroporins leads to viral attenuation in vivo, whereas data from cell culture shows involvement in the regulation of stress and inflammation. The channel activity and structure of some representative members of these viroporins have been recently characterized in some detail. In addition, searches for protein-protein interactions using yeast-two hybrid techniques have shed light on possible functional roles for their exposed cytoplasmic domains. A deeper analysis of these interactions should not only provide a more complete overview of the multiple functions of these viroporins, but also suggest novel strategies that target protein-protein interactions as much needed antivirals. These should complement current efforts to block viroporin channel activity.

C2 Domains as Protein-Protein Interaction Modules in the Ciliary Transition Zone

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Kim Remans

2014-07-01

Full Text Available RPGR-interacting protein 1 (RPGRIP1 is mutated in the eye disease Leber congenital amaurosis (LCA and its structural homolog, RPGRIP1-like (RPGRIP1L, is mutated in many different ciliopathies. Both are multidomain proteins that are predicted to interact with retinitis pigmentosa G-protein regulator (RPGR. RPGR is mutated in X-linked retinitis pigmentosa and is located in photoreceptors and primary cilia. We solved the crystal structure of the complex between the RPGR-interacting domain (RID of RPGRIP1 and RPGR and demonstrate that RPGRIP1L binds to RPGR similarly. RPGRIP1 binding to RPGR affects the interaction with PDEδ, the cargo shuttling factor for prenylated ciliary proteins. RPGRIP1-RID is a C2 domain with a canonical β sandwich structure that does not bind Ca2+ and/or phospholipids and thus constitutes a unique type of protein-protein interaction module. Judging from the large number of C2 domains in most of the ciliary transition zone proteins identified thus far, the structure presented here seems to constitute a cilia-specific module that is present in multiprotein transition zone complexes.

Protein-surface interactions on stimuli-responsive polymeric biomaterials.

Science.gov (United States)

Cross, Michael C; Toomey, Ryan G; Gallant, Nathan D

2016-03-04

Responsive surfaces: a review of the dependence of protein adsorption on the reversible volume phase transition in stimuli-responsive polymers. Specifically addressed are a widely studied subset: thermoresponsive polymers. Findings are also generalizable to other materials which undergo a similarly reversible volume phase transition. As of 2015, over 100,000 articles have been published on stimuli-responsive polymers and many more on protein-biomaterial interactions. Significantly, fewer than 100 of these have focused specifically on protein interactions with stimuli-responsive polymers. These report a clear trend of increased protein adsorption in the collapsed state compared to the swollen state. This control over protein interactions makes stimuli-responsive polymers highly useful in biomedical applications such as wound repair scaffolds, on-demand drug delivery, and antifouling surfaces. Outstanding questions are whether the protein adsorption is reversible with the volume phase transition and whether there is a time-dependence. A clear understanding of protein interactions with stimuli-responsive polymers will advance theoretical models, experimental results, and biomedical applications.

Interaction of dependent and non-dependent regions of the acutely injured lung during a stepwise recruitment manoeuvre

International Nuclear Information System (INIS)

Gómez-Laberge, Camille; Rettig, Jordan S; Arnold, John H; Wolf, Gerhard K; Smallwood, Craig D; Boyd, Theonia K

2013-01-01

The benefit of treating acute lung injury with recruitment manoeuvres is controversial. An impediment to settling this debate is the difficulty in visualizing how distinct lung regions respond to the manoeuvre. Here, regional lung mechanics were studied by electrical impedance tomography (EIT) during a stepwise recruitment manoeuvre in a porcine model with acute lung injury. The following interaction between dependent and non-dependent regions consistently occurred: atelectasis in the most dependent region was reversed only after the non-dependent region became overdistended. EIT estimates of overdistension and atelectasis were validated by histological examination of lung tissue, confirming that the dependent region was primarily atelectatic and the non-dependent region was primarily overdistended. The pulmonary pressure–volume equation, originally designed for modelling measurements at the airway opening, was adapted for EIT-based regional estimates of overdistension and atelectasis. The adaptation accurately modelled the regional EIT data from dependent and non-dependent regions (R 2 > 0.93, P < 0.0001) and predicted their interaction during recruitment. In conclusion, EIT imaging of regional lung mechanics reveals that overdistension in the non-dependent region precedes atelectasis reversal in the dependent region during a stepwise recruitment manoeuvre. (paper)

Mapping functional prion-prion protein interaction sites using prion protein based peptide-arrays

NARCIS (Netherlands)

Rigter, A.; Priem, J.; Timmers-Parohi, D.; Langeveld, J.; Bossers, A.

2009-01-01

Protein-protein interactions are at the basis of most if not all biological processes in living cells. Therefore, adapting existing techniques or developing new techniques to study interactions between proteins are of importance in elucidating which amino acid sequences contribute to these

Yeast Interacting Proteins Database: YNL258C, YKR022C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...equired for Golgi-to-ER retrograde traffic; component of the ER target site that interacts with coatomer, th...it ORF YNL258C Bait gene name DSL1 Bait description Peripheral membrane protein r

Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

Prediction of localization and interactions of apoptotic proteins

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Matula Pavel

2009-07-01

Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

Science.gov (United States)

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

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Aalt D J van Dijk

Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and

Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

Science.gov (United States)

Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

2017-06-21

For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

In silico modeling of the yeast protein and protein family interaction network

Science.gov (United States)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Towards a better understanding of the specificity of protein-protein interaction

Czech Academy of Sciences Publication Activity Database

Kysilka, Jiří; Vondrášek, Jiří

2012-01-01

Roč. 25, č. 11 (2012), s. 604-615 ISSN 0952-3499 R&D Projects: GA ČR GAP208/10/0725; GA ČR GAP302/10/0427; GA MŠk(CZ) LH11020 Institutional research plan: CEZ:AV0Z40550506; CEZ:AV0Z50520701 Keywords : protein-protein interaction * molecular recognition * x-ray structure analysis * empirical potentials * side chain-side chain interaction * interaction energy * bioinformatics Subject RIV: CE - Biochemistry Impact factor: 3.006, year: 2012

A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

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Meijing Li

2015-01-01

Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

Identification of brain-specific angiogenesis inhibitor 2 as an interaction partner of glutaminase interacting protein

International Nuclear Information System (INIS)

Zencir, Sevil; Ovee, Mohiuddin; Dobson, Melanie J.; Banerjee, Monimoy; Topcu, Zeki; Mohanty, Smita

2011-01-01

Highlights: → Brain-specific angiogenesis inhibitor 2 (BAI2) is a new partner protein for GIP. → BAI2 interaction with GIP was revealed by yeast two-hybrid assay. → Binding of BAI2 to GIP was characterized by NMR, CD and fluorescence. → BAI2 and GIP binding was mediated through the C-terminus of BAI2. -- Abstract: The vast majority of physiological processes in living cells are mediated by protein-protein interactions often specified by particular protein sequence motifs. PDZ domains, composed of 80-100 amino acid residues, are an important class of interaction motif. Among the PDZ-containing proteins, glutaminase interacting protein (GIP), also known as Tax Interacting Protein TIP-1, is unique in being composed almost exclusively of a single PDZ domain. GIP has important roles in cellular signaling, protein scaffolding and modulation of tumor growth and interacts with a number of physiological partner proteins, including Glutaminase L, β-Catenin, FAS, HTLV-1 Tax, HPV16 E6, Rhotekin and Kir 2.3. To identify the network of proteins that interact with GIP, a human fetal brain cDNA library was screened using a yeast two-hybrid assay with GIP as bait. We identified brain-specific angiogenesis inhibitor 2 (BAI2), a member of the adhesion-G protein-coupled receptors (GPCRs), as a new partner of GIP. BAI2 is expressed primarily in neurons, further expanding GIP cellular functions. The interaction between GIP and the carboxy-terminus of BAI2 was characterized using fluorescence, circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy assays. These biophysical analyses support the interaction identified in the yeast two-hybrid assay. This is the first study reporting BAI2 as an interaction partner of GIP.

Single-well monitoring of protein-protein interaction and phosphorylation-dephosphorylation events.

Science.gov (United States)

Arcand, Mathieu; Roby, Philippe; Bossé, Roger; Lipari, Francesco; Padrós, Jaime; Beaudet, Lucille; Marcil, Alexandre; Dahan, Sophie

2010-04-20

We combined oxygen channeling assays with two distinct chemiluminescent beads to detect simultaneously protein phosphorylation and interaction events that are usually monitored separately. This novel method was tested in the ERK1/2 MAP kinase pathway. It was first used to directly monitor dissociation of MAP kinase ERK2 from MEK1 upon phosphorylation and to evaluate MAP kinase phosphatase (MKP) selectivity and mechanism of action. In addition, MEK1 and ERK2 were probed with an ATP competitor and an allosteric MEK1 inhibitor, which generated distinct phosphorylation-interaction patterns. Simultaneous monitoring of protein-protein interactions and substrate phosphorylation can provide significant mechanistic insight into enzyme activity and small molecule action.

Predicting Protein-Protein Interactions Using BiGGER: Case Studies

Directory of Open Access Journals (Sweden)

Rui M. Almeida

2016-08-01

Full Text Available The importance of understanding interactomes makes preeminent the study of protein interactions and protein complexes. Traditionally, protein interactions have been elucidated by experimental methods or, with lower impact, by simulation with protein docking algorithms. This article describes features and applications of the BiGGER docking algorithm, which stands at the interface of these two approaches. BiGGER is a user-friendly docking algorithm that was specifically designed to incorporate experimental data at different stages of the simulation, to either guide the search for correct structures or help evaluate the results, in order to combine the reliability of hard data with the convenience of simulations. Herein, the applications of BiGGER are described by illustrative applications divided in three Case Studies: (Case Study A in which no specific contact data is available; (Case Study B when different experimental data (e.g., site-directed mutagenesis, properties of the complex, NMR chemical shift perturbation mapping, electron tunneling on one of the partners is available; and (Case Study C when experimental data are available for both interacting surfaces, which are used during the search and/or evaluation stage of the docking. This algorithm has been extensively used, evidencing its usefulness in a wide range of different biological research fields.

Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

Science.gov (United States)

Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

2013-01-01

We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

HCVpro: Hepatitis C virus protein interaction database

KAUST Repository

Kwofie, Samuel K.

2011-12-01

It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers. In furtherance of these goals, we have developed the hepatitis C virus protein interaction database (HCVpro) by integrating manually verified hepatitis C virus-virus and virus-human protein interactions curated from literature and databases. HCVpro is a comprehensive and integrated HCV-specific knowledgebase housing consolidated information on PPIs, functional genomics and molecular data obtained from a variety of virus databases (VirHostNet, VirusMint, HCVdb and euHCVdb), and from BIND and other relevant biology repositories. HCVpro is further populated with information on hepatocellular carcinoma (HCC) related genes that are mapped onto their encoded cellular proteins. Incorporated proteins have been mapped onto Gene Ontologies, canonical pathways, Online Mendelian Inheritance in Man (OMIM) and extensively cross-referenced to other essential annotations. The database is enriched with exhaustive reviews on structure and functions of HCV proteins, current state of drug and vaccine development and links to recommended journal articles. Users can query the database using specific protein identifiers (IDs), chromosomal locations of a gene, interaction detection methods, indexed PubMed sources as well as HCVpro, BIND and VirusMint IDs. The use of HCVpro is free and the resource can be accessed via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. © 2011 Elsevier B.V.

Structural study of surfactant-dependent interaction with protein

Energy Technology Data Exchange (ETDEWEB)

Mehan, Sumit; Aswal, Vinod K., E-mail: vkaswal@barc.gov.in [Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085 (India); Kohlbrecher, Joachim [Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen (Switzerland)

2015-06-24

Small-angle neutron scattering (SANS) has been used to study the complex structure of anionic BSA protein with three different (cationic DTAB, anionic SDS and non-ionic C12E10) surfactants. These systems form very different surfactant-dependent complexes. We show that the structure of protein-surfactant complex is initiated by the site-specific electrostatic interaction between the components, followed by the hydrophobic interaction at high surfactant concentrations. It is also found that hydrophobic interaction is preferred over the electrostatic interaction in deciding the resultant structure of protein-surfactant complexes.

Centrobin-centrosomal protein 4.1-associated protein (CPAP) interaction promotes CPAP localization to the centrioles during centriole duplication.

Science.gov (United States)

Gudi, Radhika; Zou, Chaozhong; Dhar, Jayeeta; Gao, Qingshen; Vasu, Chenthamarakshan

2014-05-30

Centriole duplication is the process by which two new daughter centrioles are generated from the proximal end of preexisting mother centrioles. Accurate centriole duplication is important for many cellular and physiological events, including cell division and ciliogenesis. Centrosomal protein 4.1-associated protein (CPAP), centrosomal protein of 152 kDa (CEP152), and centrobin are known to be essential for centriole duplication. However, the precise mechanism by which they contribute to centriole duplication is not known. In this study, we show that centrobin interacts with CEP152 and CPAP, and the centrobin-CPAP interaction is critical for centriole duplication. Although depletion of centrobin from cells did not have an effect on the centriolar levels of CEP152, it caused the disappearance of CPAP from both the preexisting and newly formed centrioles. Moreover, exogenous expression of the CPAP-binding fragment of centrobin also caused the disappearance of CPAP from both the preexisting and newly synthesized centrioles, possibly in a dominant negative manner, thereby inhibiting centriole duplication and the PLK4 overexpression-mediated centrosome amplification. Interestingly, exogenous overexpression of CPAP in the centrobin-depleted cells did not restore CPAP localization to the centrioles. However, restoration of centrobin expression in the centrobin-depleted cells led to the reappearance of centriolar CPAP. Hence, we conclude that centrobin-CPAP interaction is critical for the recruitment of CPAP to procentrioles to promote the elongation of daughter centrioles and for the persistence of CPAP on preexisting mother centrioles. Our study indicates that regulation of CPAP levels on the centrioles by centrobin is critical for preserving the normal size, shape, and number of centrioles in the cell. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

A lock-and-key model for protein–protein interactions

OpenAIRE

Morrison, Julie L.; Breitling, Rainer; Higham, Desmond J.; Gilbert, David R.

2006-01-01

Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism’s proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs,...

The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions.

Science.gov (United States)

Yates, Christopher M; Sternberg, Michael J E

2013-11-01

Non-synonymous single nucleotide polymorphisms (nsSNPs) are single base changes leading to a change to the amino acid sequence of the encoded protein. Many of these variants are associated with disease, so nsSNPs have been well studied, with studies looking at the effects of nsSNPs on individual proteins, for example, on stability and enzyme active sites. In recent years, the impact of nsSNPs upon protein-protein interactions has also been investigated, giving a greater insight into the mechanisms by which nsSNPs can lead to disease. In this review, we summarize these studies, looking at the various mechanisms by which nsSNPs can affect protein-protein interactions. We focus on structural changes that can impair interaction, changes to disorder, gain of interaction, and post-translational modifications before looking at some examples of nsSNPs at human-pathogen protein-protein interfaces and the analysis of nsSNPs from a network perspective. © 2013.

Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

Science.gov (United States)

Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

2017-11-21

Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative analysis of protein-ligand interactions by NMR.

Science.gov (United States)

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used

PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology

KAUST Repository

Li, Chuanxi; Chen, Peng; Wang, Rujing; Wang, Xiujie; Su, Yaru; Li, Jinyan

2014-01-01

Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea

Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

DEFF Research Database (Denmark)

Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

2010-01-01

proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

Communications between volunteers and health researchers during recruitment and informed consent: qualitative content analysis of email interactions.

Science.gov (United States)

Townsend, Anne; Amarsi, Zubin; Backman, Catherine L; Cox, Susan M; Li, Linda C

2011-10-13

While use of the Internet is increasingly widespread in research, little is known about the role of routine electronic mail (email) correspondence during recruitment and early volunteer-researcher interactions. To gain insight into the standpoint of volunteers we analyzed email communications in an early rheumatoid arthritis qualitative interview study. The objectives of our study were (1) to understand the perspectives and motivations of individuals who volunteered for an interview study about the experiences of early rheumatoid arthritis, and (2) to investigate the role of emails in volunteer-researcher interactions during recruitment. Between December 2007 and December 2008 we recruited 38 individuals with early rheumatoid arthritis through rheumatologist and family physician offices, arthritis Internet sites, and the Arthritis Research Centre of Canada for a (face-to-face) qualitative interview study. Interested individuals were invited to contact us via email or telephone. In this paper, we report on email communications from 12 of 29 volunteers who used email as their primary communication mode. Emails offered insights into the perspective of study volunteers. They provided evidence prospectively about recruitment and informed consent in the context of early rheumatoid arthritis. First, some individuals anticipated that participating would have mutual benefits, for themselves and the research, suggesting a reciprocal quality to volunteering. Second, volunteering for the study was strongly motivated by a need to access health services and was both a help-seeking and self-managing strategy. Third, volunteers expressed ambivalence around participation, such as how far participating would benefit them, versus more general benefits for research. Fourth, practical difficulties of negotiating symptom impact, medical appointments, and research tasks were revealed. We also reflect on how emails documented volunteer-researcher interactions, illustrating typically

Next-Generation Sequencing for Binary Protein-Protein Interactions

Directory of Open Access Journals (Sweden)

Bernhard eSuter

2015-12-01

Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

Protein annotation from protein interaction networks and Gene Ontology.

Science.gov (United States)

Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology

KAUST Repository

Li, Chuanxi

2014-01-01

Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.

Recruitment strategies should not be randomly selected: empirically improving recruitment success and diversity in developmental psychology research

Science.gov (United States)

Sugden, Nicole A.; Moulson, Margaret C.

2015-01-01

Psychological and developmental research have been critiqued for the lack of diversity of research samples. Because differences in culture, race, and ethnicity can influence participant behavior, limited diversity limits the generalizability of the findings. These differences may also impact how participants behave in response to recruitment attempts, which suggests that recruitment itself may be leveraged to increase sample diversity. The goal of the current study was to determine what factors, within a recruitment interaction, could be leveraged to increase success and diversity when recruiting families with children for developmental research. Study 1 found three factors influenced success: (1) recruitment was more successful when other potential participants were also interested (i.e., recruiters were busy), (2) recruiters of particular races were more successful than recruiters of other races, and (3) differences in success were related to what the recruiter said to engage the potential participant (i.e., the script). The latter two factors interacted, suggesting some recruiters were using less optimal scripts. To improve success rates, study 2 randomly assigned scripts to recruiters and encouraged them to recruit more vigorously during busy periods. Study 2 found that two factors influenced success: (1) some scripts were more successful than others and (2) we were more successful at recruiting non-White potential participants than White participants. These two interacted, with some scripts being more successful with White and other scripts being more successful with non-White families. This intervention significantly increased recruitment success rate by 8.1% and the overall number of families recruited by 15.3%. These findings reveal that empirically evaluating and tailoring recruitment efforts based on the most successful strategies is effective in boosting diversity through increased participation of children from non-White families. PMID:25972829

Yeast Interacting Proteins Database: YDR176W, YDL239C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle pole...ining structure at the leading edge of the prospore membrane via interaction with spindle pole body componen...DY3 Prey description Protein required for spore wall formation, thought to mediate assembly of a Don1p-conta

Coevolution of interacting fertilization proteins.

Directory of Open Access Journals (Sweden)

Nathaniel L Clark

2009-07-01

Full Text Available Reproductive proteins are among the fastest evolving in the proteome, often due to the consequences of positive selection, and their rapid evolution is frequently attributed to a coevolutionary process between interacting female and male proteins. Such a process could leave characteristic signatures at coevolving genes. One signature of coevolution, predicted by sexual selection theory, is an association of alleles between the two genes. Another predicted signature is a correlation of evolutionary rates during divergence due to compensatory evolution. We studied female-male coevolution in the abalone by resequencing sperm lysin and its interacting egg coat protein, VERL, in populations of two species. As predicted, we found intergenic linkage disequilibrium between lysin and VERL, despite our demonstration that they are not physically linked. This finding supports a central prediction of sexual selection using actual genotypes, that of an association between a male trait and its female preference locus. We also created a novel likelihood method to show that lysin and VERL have experienced correlated rates of evolution. These two signatures of coevolution can provide statistical rigor to hypotheses of coevolution and could be exploited for identifying coevolving proteins a priori. We also present polymorphism-based evidence for positive selection and implicate recent selective events at the specific structural regions of lysin and VERL responsible for their species-specific interaction. Finally, we observed deep subdivision between VERL alleles in one species, which matches a theoretical prediction of sexual conflict. Thus, abalone fertilization proteins illustrate how coevolution can lead to reproductive barriers and potentially drive speciation.

The dynamic multisite interactions between two intrinsically disordered proteins

KAUST Repository

Wu, Shaowen

2017-05-11

Protein interactions involving intrinsically disordered proteins (IDPs) comprise a variety of binding modes, from the well characterized folding upon binding to dynamic fuzzy complex. To date, most studies concern the binding of an IDP to a structured protein, while the Interaction between two IDPs is poorly understood. In this study, we combined NMR, smFRET, and molecular dynamics (MD) simulation to characterize the interaction between two IDPs, the C-terminal domain (CTD) of protein 4.1G and the nuclear mitotic apparatus (NuMA) protein. It is revealed that CTD and NuMA form a fuzzy complex with remaining structural disorder. Multiple binding sites on both proteins were identified by MD and mutagenesis studies. Our study provides an atomic scenario in which two IDPs bearing multiple binding sites interact with each other in dynamic equilibrium. The combined approach employed here could be widely applicable for investigating IDPs and their dynamic interactions.

Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling.

Directory of Open Access Journals (Sweden)

Kei Moritsugu

2014-10-01

Full Text Available Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

Levels of the E2 interacting protein TopBP1 modulate papillomavirus maintenance stage replication

International Nuclear Information System (INIS)

Kanginakudru, Sriramana; DeSmet, Marsha; Thomas, Yanique; Morgan, Iain M.; Androphy, Elliot J.

2015-01-01

The evolutionarily conserved DNA topoisomerase II beta-binding protein 1 (TopBP1) functions in DNA replication, DNA damage response, and cell survival. We analyzed the role of TopBP1 in human and bovine papillomavirus genome replication. Consistent with prior reports, TopBP1 co-localized in discrete nuclear foci and was in complex with papillomavirus E2 protein. Similar to E2, TopBP1 is recruited to the region of the viral origin of replication during G1/S and early S phase. TopBP1 knockdown increased, while over-expression decreased transient virus replication, without affecting cell cycle. Similarly, using cell lines harboring HPV-16 or HPV-31 genome, TopBP1 knockdown increased while over-expression reduced viral copy number relative to genomic DNA. We propose a model in which TopBP1 serves dual roles in viral replication: it is essential for initiation of replication yet it restricts viral copy number. - Highlights: • Protein interaction study confirmed In-situ interaction between TopBP1 and E2. • TopBP1 present at papillomavirus ori in G1/S and early S phase of cell cycle. • TopBP1 knockdown increased, over-expression reduced virus replication. • TopBP1 protein level change did not influence cell survival or cell cycle. • TopBP1 displaced from papillomavirus ori after initiation of replication

Levels of the E2 interacting protein TopBP1 modulate papillomavirus maintenance stage replication

Energy Technology Data Exchange (ETDEWEB)

Kanginakudru, Sriramana, E-mail: skangina@iu.edu [Department of Dermatology, Indiana University School of Medicine, Indianapolis, IN (United States); DeSmet, Marsha, E-mail: mdesmet@iupui.edu [Department of Dermatology, Indiana University School of Medicine, Indianapolis, IN (United States); Thomas, Yanique, E-mail: ysthomas@umail.iu.edu [Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN (United States); Morgan, Iain M., E-mail: immorgan@vcu.edu [VCU Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, Virginia (United States); Androphy, Elliot J., E-mail: eandro@iu.edu [Department of Dermatology, Indiana University School of Medicine, Indianapolis, IN (United States); Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN (United States)

2015-04-15

The evolutionarily conserved DNA topoisomerase II beta-binding protein 1 (TopBP1) functions in DNA replication, DNA damage response, and cell survival. We analyzed the role of TopBP1 in human and bovine papillomavirus genome replication. Consistent with prior reports, TopBP1 co-localized in discrete nuclear foci and was in complex with papillomavirus E2 protein. Similar to E2, TopBP1 is recruited to the region of the viral origin of replication during G1/S and early S phase. TopBP1 knockdown increased, while over-expression decreased transient virus replication, without affecting cell cycle. Similarly, using cell lines harboring HPV-16 or HPV-31 genome, TopBP1 knockdown increased while over-expression reduced viral copy number relative to genomic DNA. We propose a model in which TopBP1 serves dual roles in viral replication: it is essential for initiation of replication yet it restricts viral copy number. - Highlights: • Protein interaction study confirmed In-situ interaction between TopBP1 and E2. • TopBP1 present at papillomavirus ori in G1/S and early S phase of cell cycle. • TopBP1 knockdown increased, over-expression reduced virus replication. • TopBP1 protein level change did not influence cell survival or cell cycle. • TopBP1 displaced from papillomavirus ori after initiation of replication.

Recent progress in the development of protein-protein interaction inhibitors targeting androgen receptor-coactivator binding in prostate cancer.

Science.gov (United States)

Biron, Eric; Bédard, François

2016-07-01

The androgen receptor (AR) is a key regulator for the growth, differentiation and survival of prostate cancer cells. Identified as a primary target for the treatment of prostate cancer, many therapeutic strategies have been developed to attenuate AR signaling in prostate cancer cells. While frontline androgen-deprivation therapies targeting either the production or action of androgens usually yield favorable responses in prostate cancer patients, a significant number acquire treatment resistance. Known as the castration-resistant prostate cancer (CRPC), the treatment options are limited for this advanced stage. It has been shown that AR signaling is restored in CRPC due to many aberrant mechanisms such as AR mutations, amplification or expression of constitutively active splice-variants. Coregulator recruitment is a crucial regulatory step in AR signaling and the direct blockade of coactivator binding to AR offers the opportunity to develop therapeutic agents that would remain effective in prostate cancer cells resistant to conventional endocrine therapies. Structural analyses of the AR have identified key surfaces involved in protein-protein interaction with coregulators that have been recently used to design and develop promising AR-coactivator binding inhibitors. In this review we will discuss the design and development of small-molecule inhibitors targeting the AR-coactivator interactions for the treatment of prostate cancer. Copyright © 2015 Elsevier Ltd. All rights reserved.

A lanthipeptide library used to identify a protein-protein interaction inhibitor.

Science.gov (United States)

Yang, Xiao; Lennard, Katherine R; He, Chang; Walker, Mark C; Ball, Andrew T; Doigneaux, Cyrielle; Tavassoli, Ali; van der Donk, Wilfred A

2018-04-01

In this article we describe the production and screening of a genetically encoded library of 10 6 lanthipeptides in Escherichia coli using the substrate-tolerant lanthipeptide synthetase ProcM. This plasmid-encoded library was combined with a bacterial reverse two-hybrid system for the interaction of the HIV p6 protein with the UEV domain of the human TSG101 protein, which is a critical protein-protein interaction for HIV budding from infected cells. Using this approach, we identified an inhibitor of this interaction from the lanthipeptide library, whose activity was verified in vitro and in cell-based virus-like particle-budding assays. Given the variety of lanthipeptide backbone scaffolds that may be produced with ProcM, this method may be used for the generation of genetically encoded libraries of natural product-like lanthipeptides containing substantial structural diversity. Such libraries may be combined with any cell-based assay to identify lanthipeptides with new biological activities.

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Reciprocal carbonyl-carbonyl interactions in small molecules and proteins.

Science.gov (United States)

Rahim, Abdur; Saha, Pinaki; Jha, Kunal Kumar; Sukumar, Nagamani; Sarma, Bani Kanta

2017-07-19

Carbonyl-carbonyl n→π* interactions where a lone pair (n) of the oxygen atom of a carbonyl group is delocalized over the π* orbital of a nearby carbonyl group have attracted a lot of attention in recent years due to their ability to affect the 3D structure of small molecules, polyesters, peptides, and proteins. In this paper, we report the discovery of a "reciprocal" carbonyl-carbonyl interaction with substantial back and forth n→π* and π→π* electron delocalization between neighboring carbonyl groups. We have carried out experimental studies, analyses of crystallographic databases and theoretical calculations to show the presence of this interaction in both small molecules and proteins. In proteins, these interactions are primarily found in polyproline II (PPII) helices. As PPII are the most abundant secondary structures in unfolded proteins, we propose that these local interactions may have implications in protein folding.Carbonyl-carbonyl π* non covalent interactions affect the structure and stability of small molecules and proteins. Here, the authors carry out experimental studies, analyses of crystallographic databases and theoretical calculations to describe an additional type of carbonyl-carbonyl interaction.

[Relationship and interaction between folate and expression of methyl-CpG-binding protein 2 in cervical cancerization].

Science.gov (United States)

Li, Q L; Ding, L; Nan, J; Liu, C L; Yang, Z K; Chen, F; Liang, Y L; Wang, J T

2016-07-01

To explore the interaction between folate and the expression of methyl-CpG-binding protein 2(MeCP2)in cervical cancerization. Forty one patients diagnosed with cervical squamous cell carcinoma(SCC), 71 patients diagnosed with cervical intraepithelial neoplasm(CIN1, n=34; CIN2 +, n=37)and 61 women with normal cervix(NC)were recruited in this study. Microbiological assay was conducted to detect the levels of serum folate and RBC folate, Western blot assay and real-time PCR were performed to detect the expression levels of MeCP2 protein and mRNA, respectively. The data were analyzed by Kruskal-Wallis H test, χ(2) test, trend χ(2) test and Spearman correlation with SPSS statistical software(version 20.0), and the interaction were evaluated by using generalized multifactor dimensionality reduction(GMDR)model. The levels of serum folate(H=44.71, Pfolate(H=5.28, Pfolate level and RBC folate level(r=0.270, Pfolate level and the expression level of MeCP2 protein(serum folate: r=-0.226, P=0.003; RBC folate: r=-0.164, P=0.004). Moreover, the results by GMDR model revealed there were interaction among serum folate deficiency, RBC folate deficiency, MeCP2 protein high expression and MeCP2 mRNA high expression in SCC and CIN2 + patients. Folate deficiency and high expression of MeCP2 gene might increase the risk of cervical cancer and its precancerous lesions through interaction among serum folate deficiency, RBC folate deficiency, MeCP2 protein high expression and mRNA high expression in the progression of cervical cancerization.

Distinct Mechanism Evolved for Mycobacterial RNA Polymerase and Topoisomerase I Protein-Protein Interaction.

Science.gov (United States)

Banda, Srikanth; Cao, Nan; Tse-Dinh, Yuk-Ching

2017-09-15

We report here a distinct mechanism of interaction between topoisomerase I and RNA polymerase in Mycobacterium tuberculosis and Mycobacterium smegmatis that has evolved independently from the previously characterized interaction between bacterial topoisomerase I and RNA polymerase. Bacterial DNA topoisomerase I is responsible for preventing the hyper-negative supercoiling of genomic DNA. The association of topoisomerase I with RNA polymerase during transcription elongation could efficiently relieve transcription-driven negative supercoiling. Our results demonstrate a direct physical interaction between the C-terminal domains of topoisomerase I (TopoI-CTDs) and the β' subunit of RNA polymerase of M. smegmatis in the absence of DNA. The TopoI-CTDs in mycobacteria are evolutionarily unrelated in amino acid sequence and three-dimensional structure to the TopoI-CTD found in the majority of bacterial species outside Actinobacteria, including Escherichia coli. The functional interaction between topoisomerase I and RNA polymerase has evolved independently in mycobacteria and E. coli, with distinctively different structural elements of TopoI-CTD utilized for this protein-protein interaction. Zinc ribbon motifs in E. coli TopoI-CTD are involved in the interaction with RNA polymerase. For M. smegmatis TopoI-CTD, a 27-amino-acid tail that is rich in basic residues at the C-terminal end is responsible for the interaction with RNA polymerase. Overexpression of recombinant TopoI-CTD in M. smegmatis competed with the endogenous topoisomerase I for protein-protein interactions with RNA polymerase. The TopoI-CTD overexpression resulted in decreased survival following treatment with antibiotics and hydrogen peroxide, supporting the importance of the protein-protein interaction between topoisomerase I and RNA polymerase during stress response of mycobacteria. Copyright © 2017 Elsevier Ltd. All rights reserved.

BRCA1 interacts directly with the Fanconi anemia protein FANCA.

Science.gov (United States)

Folias, Alexandra; Matkovic, Mara; Bruun, Donald; Reid, Sonja; Hejna, James; Grompe, Markus; D'Andrea, Alan; Moses, Robb

2002-10-01

Fanconi anemia (FA) is a rare autosomal recessive disease characterized by skeletal defects, anemia, chromosomal instability and increased risk of leukemia. At the cellular level FA is characterized by increased sensitivity to agents forming interstrand crosslinks (ICL) in DNA. Six FA genes have been cloned and interactions among individual FANC proteins have been found. The FANCD2 protein co-localizes in nuclear foci with the BRCA1 protein following DNA damage and during S-phase, requiring the FANCA, C, E and G proteins to do so. This finding may reflect a direct role for the BRCA1 protein in double strand break (DSB) repair and interaction with the FANC proteins. Therefore interactions between BRCA1 and the FANC proteins were investigated. Among the known FANC proteins, we find evidence for direct interaction only between the FANCA protein and BRCA1. The evidence rests on three different tests: yeast two-hybrid analysis, coimmunoprecipitation from in vitro synthesis, and coimmunoprecipitation from cell extracts. The amino terminal portion of FANCA and the central part (aa 740-1083) of BRCA1 contain the sites of interaction. The interaction does not depend on DNA damage, thus FANCA and BRCA1 are constitutively interacting. The demonstrated interaction directly connects BRCA1 to the FA pathway of DNA repair.

Analysis of Protein-RNA and Protein-Peptide Interactions in Equine Infectious Anemia

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae-Hyung [Iowa State Univ., Ames, IA (United States)

2007-01-01

Macromolecular interactions are essential for virtually all cellular functions including signal transduction processes, metabolic processes, regulation of gene expression and immune responses. This dissertation focuses on the characterization of two important macromolecular interactions involved in the relationship between Equine Infectious Anemia Virus (EIAV) and its host cell in horse: (1) the interaction between the EIAV Rev protein and its binding site, the Rev-responsive element (RRE) and (2) interactions between equine MHC class I molecules and epitope peptides derived from EIAV proteins. EIAV, one of the most divergent members of the lentivirus family, has a single-stranded RNA genome and carries several regulatory and structural proteins within its viral particle. Rev is an essential EIAV regulatory encoded protein that interacts with the viral RRE, a specific binding site in the viral mRNA. Using a combination of experimental and computational methods, the interactions between EIAV Rev and RRE were characterized in detail. EIAV Rev was shown to have a bipartite RNA binding domain contain two arginine rich motifs (ARMs). The RRE secondary structure was determined and specific structural motifs that act as cis-regulatory elements for EIAV Rev-RRE interaction were identified. Interestingly, a structural motif located in the high affinity Rev binding site is well conserved in several diverse lentiviral genoes, including HIV-1. Macromolecular interactions involved in the immune response of the horse to EIAV infection were investigated by analyzing complexes between MHC class I proteins and epitope peptides derived from EIAV Rev, Env and Gag proteins. Computational modeling results provided a mechanistic explanation for the experimental finding that a single amino acid change in the peptide binding domain of the quine MHC class I molecule differentially affectes the recognitino of specific epitopes by EIAV-specific CTL. Together, the findings in this

The C-terminal region of A-kinase anchor protein 350 (AKAP350A) enables formation of microtubule-nucleation centers and interacts with pericentriolar proteins.

Science.gov (United States)

Kolobova, Elena; Roland, Joseph T; Lapierre, Lynne A; Williams, Janice A; Mason, Twila A; Goldenring, James R

2017-12-15

Microtubules in animal cells assemble (nucleate) from both the centrosome and the cis-Golgi cisternae. A-kinase anchor protein 350 kDa (AKAP350A, also called AKAP450/CG-NAP/AKAP9) is a large scaffolding protein located at both the centrosome and Golgi apparatus. Previous findings have suggested that AKAP350 is important for microtubule dynamics at both locations, but how this scaffolding protein assembles microtubule nucleation machinery is unclear. Here, we found that overexpression of the C-terminal third of AKAP350A, enhanced GFP-AKAP350A(2691-3907), induces the formation of multiple microtubule-nucleation centers (MTNCs). Nevertheless, these induced MTNCs lacked "true" centriole proteins, such as Cep135. Mapping analysis with AKAP350A truncations demonstrated that AKAP350A contains discrete regions responsible for promoting or inhibiting the formation of multiple MTNCs. Moreover, GFP-AKAP350A(2691-3907) recruited several pericentriolar proteins to MTNCs, including γ-tubulin, pericentrin, Cep68, Cep170, and Cdk5RAP2. Proteomic analysis indicated that Cdk5RAP2 and Cep170 both interact with the microtubule nucleation-promoting region of AKAP350A, whereas Cep68 interacts with the distal C-terminal AKAP350A region. Yeast two-hybrid assays established a direct interaction of Cep170 with AKAP350A. Super-resolution and deconvolution microscopy analyses were performed to define the association of AKAP350A with centrosomes, and these studies disclosed that AKAP350A spans the bridge between centrioles, co-localizing with rootletin and Cep68 in the linker region. siRNA-mediated depletion of AKAP350A caused displacement of both Cep68 and Cep170 from the centrosome. These results suggest that AKAP350A acts as a scaffold for factors involved in microtubule nucleation at the centrosome and coordinates the assembly of protein complexes associating with the intercentriolar bridge.

Hepatitis C Virus Proteins Interact with the Endosomal Sorting Complex Required for Transport (ESCRT) Machinery via Ubiquitination To Facilitate Viral Envelopment.

Science.gov (United States)

Barouch-Bentov, Rina; Neveu, Gregory; Xiao, Fei; Beer, Melanie; Bekerman, Elena; Schor, Stanford; Campbell, Joseph; Boonyaratanakornkit, Jim; Lindenbach, Brett; Lu, Albert; Jacob, Yves; Einav, Shirit

2016-11-01

Enveloped viruses commonly utilize late-domain motifs, sometimes cooperatively with ubiquitin, to hijack the endosomal sorting complex required for transport (ESCRT) machinery for budding at the plasma membrane. However, the mechanisms underlying budding of viruses lacking defined late-domain motifs and budding into intracellular compartments are poorly characterized. Here, we map a network of hepatitis C virus (HCV) protein interactions with the ESCRT machinery using a mammalian-cell-based protein interaction screen and reveal nine novel interactions. We identify HRS (hepatocyte growth factor-regulated tyrosine kinase substrate), an ESCRT-0 complex component, as an important entry point for HCV into the ESCRT pathway and validate its interactions with the HCV nonstructural (NS) proteins NS2 and NS5A in HCV-infected cells. Infectivity assays indicate that HRS is an important factor for efficient HCV assembly. Specifically, by integrating capsid oligomerization assays, biophysical analysis of intracellular viral particles by continuous gradient centrifugations, proteolytic digestion protection, and RNase digestion protection assays, we show that HCV co-opts HRS to mediate a late assembly step, namely, envelopment. In the absence of defined late-domain motifs, K63-linked polyubiquitinated lysine residues in the HCV NS2 protein bind the HRS ubiquitin-interacting motif to facilitate assembly. Finally, ESCRT-III and VPS/VTA1 components are also recruited by HCV proteins to mediate assembly. These data uncover involvement of ESCRT proteins in intracellular budding of a virus lacking defined late-domain motifs and a novel mechanism by which HCV gains entry into the ESCRT network, with potential implications for other viruses. Viruses commonly bud at the plasma membrane by recruiting the host ESCRT machinery via conserved motifs termed late domains. The mechanism by which some viruses, such as HCV, bud intracellularly is, however, poorly characterized. Moreover, whether

Identification of proteins that may directly interact with human RPA.

Science.gov (United States)

Nakaya, Ryou; Takaya, Junichiro; Onuki, Takeshi; Moritani, Mariko; Nozaki, Naohito; Ishimi, Yukio

2010-11-01

RPA, which consisted of three subunits (RPA1, 2 and 3), plays essential roles in DNA transactions. At the DNA replication forks, RPA binds to single-stranded DNA region to stabilize the structure and to assemble other replication proteins. Interactions between RPA and several replication proteins have been reported but the analysis is not comprehensive. We systematically performed the qualitative analysis to identify RPA interaction partners to understand the protein-protein interaction at the replication forks. We expressed in insect cells the three subunits of human RPA, together with one replication protein, which is present at the forks under normal conditions and/or under the replication stress conditions, to examine the interaction. Among 30 proteins examined in total, it was found that at least 14 proteins interacted with RPA. RPA interacted with MCM3-7, MCM-BP and CDC45 proteins among the proteins that play roles in the initiation and the elongation of the DNA replication. RPA bound with TIPIN, CLASPIN and RAD17, which are involved in the DNA replication checkpoint functions. RPA also bound with cyclin-dependent kinases and an amino-terminal fragment of Rb protein that negatively regulates DNA replication. These results suggest that RPA interacts with the specific proteins among those that play roles in the regulation of the replication fork progression.

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Recruitment of EB1, a Master Regulator of Microtubule Dynamics, to the Surface of the Theileria annulata Schizont

KAUST Repository

Woods, Kerry L.

2013-05-09

The apicomplexan parasite Theileria annulata transforms infected host cells, inducing uncontrolled proliferation and clonal expansion of the parasitized cell population. Shortly after sporozoite entry into the target cell, the surrounding host cell membrane is dissolved and an array of host cell microtubules (MTs) surrounds the parasite, which develops into the transforming schizont. The latter does not egress to invade and transform other cells. Instead, it remains tethered to host cell MTs and, during mitosis and cytokinesis, engages the cell\\'s astral and central spindle MTs to secure its distribution between the two daughter cells. The molecular mechanism by which the schizont recruits and stabilizes host cell MTs is not known. MT minus ends are mostly anchored in the MT organizing center, while the plus ends explore the cellular space, switching constantly between phases of growth and shrinkage (called dynamic instability). Assuming the plus ends of growing MTs provide the first point of contact with the parasite, we focused on the complex protein machinery associated with these structures. We now report how the schizont recruits end-binding protein 1 (EB1), a central component of the MT plus end protein interaction network and key regulator of host cell MT dynamics. Using a range of in vitro experiments, we demonstrate that T. annulata p104, a polymorphic antigen expressed on the schizont surface, functions as a genuine EB1-binding protein and can recruit EB1 in the absence of any other parasite proteins. Binding strictly depends on a consensus SxIP motif located in a highly disordered C-terminal region of p104. We further show that parasite interaction with host cell EB1 is cell cycle regulated. This is the first description of a pathogen-encoded protein to interact with EB1 via a bona-fide SxIP motif. Our findings provide important new insight into the mode of interaction between Theileria and the host cell cytoskeleton. 2013 Woods et al.

Recruitment of EB1, a master regulator of microtubule dynamics, to the surface of the Theileria annulata schizont.

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Kerry L Woods

2013-05-01

Full Text Available The apicomplexan parasite Theileria annulata transforms infected host cells, inducing uncontrolled proliferation and clonal expansion of the parasitized cell population. Shortly after sporozoite entry into the target cell, the surrounding host cell membrane is dissolved and an array of host cell microtubules (MTs surrounds the parasite, which develops into the transforming schizont. The latter does not egress to invade and transform other cells. Instead, it remains tethered to host cell MTs and, during mitosis and cytokinesis, engages the cell's astral and central spindle MTs to secure its distribution between the two daughter cells. The molecular mechanism by which the schizont recruits and stabilizes host cell MTs is not known. MT minus ends are mostly anchored in the MT organizing center, while the plus ends explore the cellular space, switching constantly between phases of growth and shrinkage (called dynamic instability. Assuming the plus ends of growing MTs provide the first point of contact with the parasite, we focused on the complex protein machinery associated with these structures. We now report how the schizont recruits end-binding protein 1 (EB1, a central component of the MT plus end protein interaction network and key regulator of host cell MT dynamics. Using a range of in vitro experiments, we demonstrate that T. annulata p104, a polymorphic antigen expressed on the schizont surface, functions as a genuine EB1-binding protein and can recruit EB1 in the absence of any other parasite proteins. Binding strictly depends on a consensus SxIP motif located in a highly disordered C-terminal region of p104. We further show that parasite interaction with host cell EB1 is cell cycle regulated. This is the first description of a pathogen-encoded protein to interact with EB1 via a bona-fide SxIP motif. Our findings provide important new insight into the mode of interaction between Theileria and the host cell cytoskeleton.

PIWI Proteins and PIWI-Interacting RNA

DEFF Research Database (Denmark)

Han, Yi Neng; Li, Yuan; Xia, Sheng Qiang

2017-01-01

tissue types as well and play important roles in transposon silencing, epigenetic regulation, gene and protein regulation, genome rearrangement, spermatogenesis and germ stem-cell maintenance. PIWI proteins were first discovered in Drosophila and they play roles in spermatogenesis, germline stem-cell......P-Element induced wimpy testis (PIWI)-interacting RNAs (piRNAs) are a type of noncoding RNAs (ncRNAs) and interact with PIWI proteins. piRNAs were primarily described in the germline, but emerging evidence revealed that piRNAs are expressed in a tissue-specific manner among multiple human somatic...... maintenance, self-renewal, retrotransposons silencing and the male germline mobility control. A growing number of studies have demonstrated that several piRNA and PIWI proteins are aberrantly expressed in various kinds of cancers and may probably serve as a novel biomarker and therapeutic target for cancer...

Hepatitis C Virus Proteins Interact with the Endosomal Sorting Complex Required for Transport (ESCRT Machinery via Ubiquitination To Facilitate Viral Envelopment

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Rina Barouch-Bentov

2016-11-01

Full Text Available Enveloped viruses commonly utilize late-domain motifs, sometimes cooperatively with ubiquitin, to hijack the endosomal sorting complex required for transport (ESCRT machinery for budding at the plasma membrane. However, the mechanisms underlying budding of viruses lacking defined late-domain motifs and budding into intracellular compartments are poorly characterized. Here, we map a network of hepatitis C virus (HCV protein interactions with the ESCRT machinery using a mammalian-cell-based protein interaction screen and reveal nine novel interactions. We identify HRS (hepatocyte growth factor-regulated tyrosine kinase substrate, an ESCRT-0 complex component, as an important entry point for HCV into the ESCRT pathway and validate its interactions with the HCV nonstructural (NS proteins NS2 and NS5A in HCV-infected cells. Infectivity assays indicate that HRS is an important factor for efficient HCV assembly. Specifically, by integrating capsid oligomerization assays, biophysical analysis of intracellular viral particles by continuous gradient centrifugations, proteolytic digestion protection, and RNase digestion protection assays, we show that HCV co-opts HRS to mediate a late assembly step, namely, envelopment. In the absence of defined late-domain motifs, K63-linked polyubiquitinated lysine residues in the HCV NS2 protein bind the HRS ubiquitin-interacting motif to facilitate assembly. Finally, ESCRT-III and VPS/VTA1 components are also recruited by HCV proteins to mediate assembly. These data uncover involvement of ESCRT proteins in intracellular budding of a virus lacking defined late-domain motifs and a novel mechanism by which HCV gains entry into the ESCRT network, with potential implications for other viruses.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

International Nuclear Information System (INIS)

Nielsen, Anders Lade

2009-01-01

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of γ-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as β-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Anders Lade, E-mail: aln@humgen.au.dk [Department of Human Genetics, The Bartholin Building, University of Aarhus, DK-8000 Aarhus C (Denmark)

2009-10-23

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of {gamma}-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as {beta}-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

Science.gov (United States)

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

EMMPRIN (CD147/basigin) mediates platelet-monocyte interactions in vivo and augments monocyte recruitment to the vascular wall.

Science.gov (United States)

Schulz, C; von Brühl, M-L; Barocke, V; Cullen, P; Mayer, K; Okrojek, R; Steinhart, A; Ahmad, Z; Kremmer, E; Nieswandt, B; Frampton, J; Massberg, S; Schmidt, R

2011-05-01

Platelets play a central role in hemostasis, in inflammatory diseases such as atherosclerosis, and during thrombus formation following vascular injury. Thereby, platelets interact intensively with monocytes and enhance their recruitment to the vascular wall. To investigate the role of the extracellular matrix metalloproteinase inducer (EMMPRIN) in platelet-monocyte interactions. Isolated human monocytes were perfused in vitro over firmly adherent platelets to allow investigation of the role of EMMPRIN in platelet-monocyte interactions under flow conditions. Monocytes readily bound to surface-adherent platelets. Both antibody blockade and gene silencing of monocyte EMMPRIN substantially attenuated firm adhesion of monocytes to platelets at arterial and venous shear rates. In vivo, platelet interactions with the murine monocyte cell line ANA-1 were significantly decreased when ANA-1 cells were pretreated with EMMPRIN-silencing small interfering RNA prior to injection into wild-type mice. Using intravital microscopy, we showed that recruitment of EMMPRIN-silenced ANA-1 to the injured carotid artery was significantly reduced as compared with control cells. Further silencing of EMMPRIN resulted in significantly fewer ANA-1-platelet aggregates in the mouse circulation as determined by flow cytometry. Finally, we identified glycoprotein (GP)VI as a critical corresponding receptor on platelets that mediates interaction with monocyte EMMPRIN. Thus, blocking of GPVI inhibited the effect of EMMPRIN on firm monocyte adhesion to platelets under arterial flow conditions in vitro, and abrogated EMMPRIN-mediated platelet-monocyte aggregate formation in vivo. EMMPRIN supports platelet-monocyte interactions and promotes monocyte recruitment to the arterial wall. Therefore, EMMPRIN might represent a novel target to reduce vascular inflammation and atherosclerotic lesion development. © 2011 International Society on Thrombosis and Haemostasis.

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

Science.gov (United States)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-07-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

Interactions between whey proteins and kaolinite surfaces

Energy Technology Data Exchange (ETDEWEB)

Barral, S. [Department of Chemical Engineering and Environmental Technology, University of Oviedo, Julian Claveria 8, 33006 Oviedo (Spain); Villa-Garcia, M.A. [Department of Organic and Inorganic Chemistry, University of Oviedo, Julian Claveria 8, 33006 Oviedo (Spain)], E-mail: mavg@uniovi.es; Rendueles, M. [Project Management Area, University of Oviedo, Independencia 13, 33004 Oviedo (Spain); Diaz, M. [Department of Chemical Engineering and Environmental Technology, University of Oviedo, Julian Claveria 8, 33006 Oviedo (Spain)

2008-07-15

The nature of the interactions between whey proteins and kaolinite surfaces was investigated by adsorption-desorption experiments at room temperature, performed at the isoelectric point (IEP) of the proteins and at pH 7. It was found that kaolinite is a strong adsorbent for proteins, reaching the maximum adsorption capacity at the IEP of each protein. At pH 7.0, the retention capacity decreased considerably. The adsorption isotherms showed typical Langmuir characteristics. X-ray diffraction data for the protein-kaolinite complexes showed that protein molecules were not intercalated in the mineral structure, but immobilized at the external surfaces and the edges of the kaolinite. Fourier transform IR results indicate the absence of hydrogen bonding between kaolinite surfaces and the polypeptide chain. The adsorption patterns appear to be related to electrostatic interactions, although steric effects should be also considered.

Interactions between whey proteins and kaolinite surfaces

International Nuclear Information System (INIS)

Barral, S.; Villa-Garcia, M.A.; Rendueles, M.; Diaz, M.

2008-01-01

The nature of the interactions between whey proteins and kaolinite surfaces was investigated by adsorption-desorption experiments at room temperature, performed at the isoelectric point (IEP) of the proteins and at pH 7. It was found that kaolinite is a strong adsorbent for proteins, reaching the maximum adsorption capacity at the IEP of each protein. At pH 7.0, the retention capacity decreased considerably. The adsorption isotherms showed typical Langmuir characteristics. X-ray diffraction data for the protein-kaolinite complexes showed that protein molecules were not intercalated in the mineral structure, but immobilized at the external surfaces and the edges of the kaolinite. Fourier transform IR results indicate the absence of hydrogen bonding between kaolinite surfaces and the polypeptide chain. The adsorption patterns appear to be related to electrostatic interactions, although steric effects should be also considered

Cell penetrating peptides to dissect host-pathogen protein-protein interactions in Theileria -transformed leukocytes

KAUST Repository

Haidar, Malak

2017-09-08

One powerful application of cell penetrating peptides is the delivery into cells of molecules that function as specific competitors or inhibitors of protein-protein interactions. Ablating defined protein-protein interactions is a refined way to explore their contribution to a particular cellular phenotype in a given disease context. Cell-penetrating peptides can be synthetically constrained through various chemical modifications that stabilize a given structural fold with the potential to improve competitive binding to specific targets. Theileria-transformed leukocytes display high PKA activity, but PKAis an enzyme that plays key roles in multiple cellular processes; consequently genetic ablation of kinase activity gives rise to a myriad of confounding phenotypes. By contrast, ablation of a specific kinase-substrate interaction has the potential to give more refined information and we illustrate this here by describing how surgically ablating PKA interactions with BAD gives precise information on the type of glycolysis performed by Theileria-transformed leukocytes. In addition, we provide two other examples of how ablating specific protein-protein interactions in Theileria-infected leukocytes leads to precise phenotypes and argue that constrained penetrating peptides have great therapeutic potential to combat infectious diseases in general.

A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling

DEFF Research Database (Denmark)

Blagoev, B.; Kratchmarova, I.; Ong, S.E.

2003-01-01

Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we em...

Semantic integration to identify overlapping functional modules in protein interaction networks

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Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

A Physical Interaction Network of Dengue Virus and Human Proteins*

Science.gov (United States)

Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

2011-01-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

A physical interaction network of dengue virus and human proteins.

Science.gov (United States)

Khadka, Sudip; Vangeloff, Abbey D; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J; Perera, Rushika; LaCount, Douglas J

2011-12-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection.

A coevolution analysis for identifying protein-protein interactions by Fourier transform

Science.gov (United States)

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

Directory of Open Access Journals (Sweden)

Changchuan Yin

Full Text Available Protein-protein interactions (PPIs play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA; however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40. The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI.

Cell Cycle-Dependent Recruitment of Polycomb Proteins to the ASNS Promoter Counteracts C/ebp-Mediated Transcriptional Activation in Bombyx mori

Science.gov (United States)

Li, Zhiqing; Cheng, Daojun; Mon, Hiroaki; Zhu, Li; Xu, Jian; Tatsuke, Tsuneyuki; Lee, Jae Man; Xia, Qingyou; Kusakabe, Takahiro

2013-01-01

Epigenetic modifiers and transcription factors contribute to developmentally programmed gene expression. Here, we establish a functional link between epigenetic regulation by Polycomb group (PcG) proteins and transcriptional regulation by C/ebp that orchestrates the correct expression of Bombyx mori asparagine synthetase (BmASNS), a gene involved in the biosynthesis of asparagine. We show that the cis-regulatory elements of YY1-binding motifs and the CpG island present on the BmASNS promoter are required for the recruitment of PcG proteins and the subsequent deposition of the epigenetic repression mark H3K27me3. RNAi-mediated knockdown of PcG genes leads to derepression of the BmASNS gene via the recruitment of activators, including BmC/ebp, to the promoter. Intriguingly, we find that PcG proteins and BmC/ebp can dynamically modulate the transcriptional output of the BmASNS target in a cell cycle-dependent manner. It will be essential to suppress BmASNS expression by PcG proteins at the G2/M phase of the cell cycle in the presence of BmC/ebp activator. Thus, our results provide a novel insight into the molecular mechanism underlying the recruitment and regulation of the PcG system at a discrete gene locus in Bombyx mori. PMID:23382816